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@article{HatcliffEtAl2009,
	Abstract = {In August of 2007 and December of 2007, North American academic researchers,
	industry representatives and regulators were invited to meetings
	in Washington and Minneapolis, respectively, with the goal of forming
	a Software Certification Consortium (SCC). At the first meeting,
	objectives were established for the consortium and a certification
	grand challenge was issued. At the second meeting, all participants
	were asked to complete the statement: ``Software certification is
	hard because . . .''. The group then synthesized the results into
	a ``Top 9'' list by means of discussion and voting. In this article,
	we describe the goals that we believe should be the goals of SCC,
	via details of these Top 9 hurdles that are preventing us from making
	software certification part of the mainstream},
	Author = {Hatcliff, John and Heimdahl, Mats and Lawford, Mark and Maibaum, Tom and Wassyng, Alan and Wurden, Fred},
	Date-Added = {2017-08-15 05:15:35 +0000},
	Date-Modified = {2017-08-15 05:15:35 +0000},
	Doi = {10.1016/j.entcs.2009.09.002},
	File = {:Users/gonzalo/McSCert/scc/ref/McSCert/A Software Certification Consortium and its Top 9 Hurdles (safecert08).pdf:pdf},
	Issn = {1571-0661},
	Journal = {Electronic Notes in Theoretical Computer Science},
	Keywords = {formal methods,objectives,projects,scc,software certification consortium},
	Number = {4},
	Pages = {11--17},
	Publisher = {Elsevier},
	Title = {A Software Certification Consortium and its Top 9 Hurdles},
	Url = {http://linkinghub.elsevier.com/retrieve/pii/S1571066109003570},
	Volume = {238},
	Year = {2009},
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	Bdsk-Url-1 = {http://dx.doi.org/10.1016/j.entcs.2009.09.002}}

@article{CrickAndHall2014,
	Author = {Tom Crick and Benjamin A. Hall and Samin Ishtiaq},
	Bibsource = {dblp computer science bibliography, http://dblp.org},
	Biburl = {http://dblp.uni-trier.de/rec/bib/journals/corr/CrickHI14},
	Date-Added = {2017-08-15 05:11:16 +0000},
	Date-Modified = {2017-08-15 05:11:16 +0000},
	Journal = {CoRR},
	Timestamp = {Fri, 01 Aug 2014 13:50:01 +0200},
	Title = {``{C}an {I} Implement Your Algorithm?'': {A} Model for Reproducible Research Software},
	Url = {http://arxiv.org/abs/1407.5981},
	Volume = {abs/1407.5981},
	Year = {2014},
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@inproceedings{SmithMcCutchanAndCao2007,
	Address = {Montr\'{e}al, Qu\'{e}bec},
	Author = {W. Spencer Smith and John McCutchan and Fang Cao},
	Booktitle = {7$^{th}$ OOPSLA Workshop on Domain Specific Modelling ({DSM}'07)},
	Date-Added = {2017-08-11 11:56:25 +0000},
	Date-Modified = {2017-08-11 11:56:25 +0000},
	Editor = {Jonathan Sprinkle and Jeff Gray and Matti Rossi and Juha-Pekka Tolvanen},
	Local-Url = {/Users/smiths/Work/Research/Papers/OOPSLA_Workshop2007/ProgFamiliesInSciComp_CameraReady.pdf},
	Month = {October},
	Pages = {39--47},
	Title = {Program Families in Scientific Computing},
	Year = {2007},
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@article{Carette2006,
	Author = {Jacques Carette},
	Date-Added = {2017-08-11 11:56:17 +0000},
	Date-Modified = {2017-08-11 11:56:17 +0000},
	Journal = {Science of Computer Programming},
	Keywords = {MetaOCaml, linear algebra, genericity, generative, staging},
	Local-Url = {file://localhost/Users/smiths/LongTermArchives/Work/Research/References/ScientificComputing/Carette2006.pdf},
	Number = {1},
	Pages = {3--24},
	Title = {Gaussian Elimination: A case study in efficient genericity with {M}eta{OC}aml},
	Volume = {62},
	Year = {2006},
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@techreport{Costabile2012,
	Address = {Hamilton, ON, Canada},
	Author = {Jason Costabile},
	Date-Added = {2017-08-11 10:47:39 +0000},
	Date-Modified = {2017-08-11 10:50:30 +0000},
	Institution = {McMaster University, Department of Computing and Software},
	Month = {August},
	Title = {{GOOL}: A Generic {OO} Language},
	Type = {Report},
	Year = {2012}}

@inproceedings{SmithJegatheesanAndKelly2016,
	Author = {W. Spencer Smith and Thulasi Jegatheesan and Diane F. Kelly},
	Booktitle = {Proceedings of the Fourth International Workshop on Software Engineering for High Performance Computing in Computational Science and Engineering (SE-HPCCE)},
	Date-Added = {2017-08-01 22:45:59 +0000},
	Date-Modified = {2017-08-01 22:45:59 +0000},
	Month = {November},
	Note = {8 pp},
	Title = {Advantages, Disadvantages and Misunderstandings About Document Driven Design for Scientific Software},
	Year = {2016},
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	Bdsk-Url-1 = {http://se4science.org/workshops/sehpccse16/cfp.htm}}

@inproceedings{SzymczakEtAl2016,
	Address = {Austin, Texas, United States},
	Author = {Daniel Szymczak and W. Spencer Smith and Jacques Carette},
	Booktitle = {Proceedings of SE4Science'16 in conjunction with the International Conference on Software Engineering (ICSE)},
	Date-Added = {2017-08-01 22:45:08 +0000},
	Date-Modified = {2017-08-01 22:45:08 +0000},
	Month = {May},
	Note = {4 pp.},
	Organization = {In conjunction with ICSE 2016},
	Title = {Position Paper: A Knowledge-Based Approach to Scientific Software Development},
	Year = {2016},
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@inproceedings{Parnas2010,
	Author = {David Lorge Parnas},
	Bibsource = {dblp computer science bibliography, http://dblp.org},
	Biburl = {http://dblp.uni-trier.de/rec/bib/conf/birthday/Parnas10},
	Booktitle = {The Future of Software Engineering},
	Date-Added = {2017-08-01 21:00:07 +0000},
	Date-Modified = {2017-08-01 21:00:07 +0000},
	Doi = {10.1007/978-3-642-15187-3_8},
	Pages = {125--148},
	Timestamp = {Tue, 30 Aug 2011 14:09:42 +0200},
	Title = {Precise Documentation: The Key to Better Software},
	Url = {http://dx.doi.org/10.1007/978-3-642-15187-3_8},
	Year = {2010},
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	Bdsk-Url-1 = {http://dx.doi.org/10.1007/978-3-642-15187-3_8}}

@inproceedings{IonescuAndJansson2013,
	Author = {Cezar Ionescu and Patrik Jansson},
	Booktitle = {{Revised Selected Papers of the 24th International Symposium on Implementation and Application of Functional Languages}},
	Date-Added = {2017-08-01 20:59:50 +0000},
	Date-Modified = {2017-08-01 20:59:50 +0000},
	Doi = {10.1007/978-3-642-41582-1_9},
	Pages = {140--156},
	Publisher = {{Springer International Publishing}},
	Series = {{Lecture Notes in Computer Science}},
	Title = {{Dependently-Typed Programming in Scientific Computing --- Examples from Economic Modelling}},
	Volume = 8241,
	Year = 2012,
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	Bdsk-Url-1 = {http://dx.doi.org/10.1007/978-3-642-41582-1_9}}

@mastersthesis{Jegatheesan2016,
	Address = {Hamilton, Ontario, Canada},
	Author = {Thulasi Jegatheesan},
	Date-Added = {2017-08-01 20:59:21 +0000},
	Date-Modified = {2017-08-01 20:59:21 +0000},
	Month = {July},
	School = {McMaster University},
	Title = {Case Studies in Document Driven Design of Scientific Computing Software},
	Year = {2016},
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@book{Roache1998,
	Address = {Albuquerque, New Mexico},
	Author = {Patrick J. Roache},
	Date-Added = {2017-07-25 18:29:45 +0000},
	Date-Modified = {2017-07-25 18:29:45 +0000},
	Publisher = {Hermosa Publishers},
	Title = {Verification and Validation in Computational Science and Engineering},
	Year = {1998}}

@inproceedings{CarverEtAl2007,
	Address = {Washington, DC, USA},
	Author = {Jeffrey C. Carver and Richard P. Kendall and Susan E. Squires and Douglass E. Post},
	Booktitle = {ICSE '07: Proceedings of the 29th International Conference on Software Engineering},
	Date-Added = {2017-07-25 18:29:34 +0000},
	Date-Modified = {2017-07-25 18:29:34 +0000},
	Doi = {http://dx.doi.org/10.1109/ICSE.2007.77},
	Isbn = {0-7695-2828-7},
	Local-Url = {file://localhost/Users/smiths/LongTermArchives/Work/Research/References/SciCompAndSoftEng/CarverEtAl2007.pdf},
	Pages = {550--559},
	Publisher = {IEEE Computer Society},
	Title = {Software Development Environments for Scientific and Engineering Software: A Series of Case Studies},
	Year = {2007},
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	Bdsk-Url-1 = {http://dx.doi.org/10.1109/ICSE.2007.77}}

@techreport{CNSC2000,
	Author = {{Canadian Nuclear Safety Commission (CNSC)}},
	Date-Added = {2017-07-25 18:28:48 +0000},
	Date-Modified = {2017-07-25 18:28:48 +0000},
	Institution = {Minister of Public Works and Government Services Canada},
	Month = {October},
	Number = {G-149},
	Title = {Computer Programs Used in Design and Safety Analyses of Nuclear Power Plants and Research Reactors},
	Year = {2000},
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@article{SmithAndKoothoor2016,
	Abstract = {This paper presents a documentation and development method to facilitate the certification of scientific computing software used in the safety analysis of nuclear facilities. To study the problems faced during quality assurance and certification activities, a case study was performed on legacy software used for thermal analysis of a fuelpin in a nuclear reactor. Although no errors were uncovered in the code, 27 issues of incompleteness and inconsistency were found with the documentation. This work proposes that software documentation follow a rational process, which includes a software requirements specification following a template that is reusable, maintainable, and understandable. To develop the design and implementation, this paper suggests literate programming as an alternative to traditional structured programming. Literate programming allows for documenting of numerical algorithms and code together in what is termed the literate programmer's manual. This manual is developed with explicit traceability to the software requirements specification. The traceability between the theory, numerical algorithms, and implementation facilitates achieving completeness and consistency, as well as simplifies the process of verification and the associated certification. },
	Author = {W. Spencer Smith and Nirmitha Koothoor},
	Date-Added = {2017-07-25 18:22:02 +0000},
	Date-Modified = {2017-07-25 18:22:02 +0000},
	Doi = {http://dx.doi.org/10.1016/j.net.2015.11.008},
	Issn = {1738-5733},
	Journal = {Nuclear Engineering and Technology},
	Keywords = {Software Quality},
	Month = {April},
	Number = {2},
	Pages = {404-418},
	Title = {A Document-Driven Method for Certifying Scientific Computing Software for Use in Nuclear Safety Analysis},
	Url = {http://www.sciencedirect.com/science/article/pii/S1738573315002582},
	Volume = {48},
	Year = {2016},
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	Bdsk-Url-1 = {http://www.sciencedirect.com/science/article/pii/S1738573315002582},
	Bdsk-Url-2 = {http://dx.doi.org/10.1016/j.net.2015.11.008}}

@inproceedings{SmithAndLai2005,
	Address = {Paris, France},
	Author = {W. Spencer Smith and Lei Lai},
	Booktitle = {Proceedings of the First International Workshop on Situational Requirements Engineering Processes -- Methods, Techniques and Tools to Support Situation-Specific Requirements Engineering Processes, SREP'05},
	Date-Added = {2017-07-11 19:56:04 +0000},
	Date-Modified = {2017-07-11 19:56:04 +0000},
	Editor = {J. Ralyt\'{e} and P. \.{A}gerfalk and N. Kraiem},
	Local-Url = {file://localhost/Users/smiths/Work/Research/Papers/SREP05/SREP05_ReformatAndRevise/SmithAndLai_2005.pdf},
	Organization = {In conjunction with 13th IEEE International Requirements Engineering Conference},
	Pages = {107--121},
	Title = {A New Requirements Template for Scientific Computing},
	Year = {2005},
	Bdsk-File-1 = {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}}

@article{SmithEtAl2007,
	Author = {W. Spencer Smith and Lei Lai and Ridha Khedri},
	Date-Added = {2017-07-11 19:56:01 +0000},
	Date-Modified = {2017-07-11 19:56:01 +0000},
	Journal = {Reliable Computing, Special Issue on Reliable Engineering Computation},
	Local-Url = {/Users/smiths/Work/Research/Papers/ReliableComputing/SmithLaiAndKhedri2007fulltext.pdf},
	Month = {February},
	Number = {1},
	Pages = {83--107},
	Title = {Requirements Analysis for Engineering Computation: A Systematic Approach for Improving Software Reliability},
	Volume = {13},
	Year = {2007},
	Bdsk-File-1 = {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}}

@article{ParnasAndClements1986,
	Author = {David L. Parnas and P.C. Clements},
	Date-Added = {2015-03-19 19:27:43 +0000},
	Date-Modified = {2015-03-19 19:27:43 +0000},
	Journal = {IEEE Transactions on Software Engineering},
	Number = {2},
	Pages = {251--257},
	Title = {A Rational Design Process: How and Why to Fake it},
	Volume = {12},
	Year = {February 1986},
	Bdsk-File-1 = {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}}

@inproceedings{CaretteEtAl2011,
  title={A generative geometric kernel},
  author={Carette, Jacques and Elsheikh, Mustafa and Smith, Spencer},
  booktitle={Proceedings of the 20th ACM SIGPLAN workshop on Partial evaluation and program manipulation},
  pages={53--62},
  year={2011},
  organization={ACM}
}

repository: JacquesCarette/Drasil

repo_name: JacquesCarette/Drasil

gha_language: Haskell


text:
@proceedings{ws-2017-representation,
    title = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    editor = "Blunsom, Phil  and
      Bordes, Antoine  and
      Cho, Kyunghyun  and
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      Grefenstette, Edward  and
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    month = aug,
    year = "2017",
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@inproceedings{gamallo-2017-sense,
    title = "Sense Contextualization in a Dependency-Based Compositional Distributional Model",
    author = "Gamallo, Pablo",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
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    pages = "1--9",
}
@inproceedings{horn-2017-context,
    title = "Context encoders as a simple but powerful extension of word2vec",
    author = "Horn, Franziska",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2602",
    doi = "10.18653/v1/W17-2602",
    pages = "10--14",
}
@inproceedings{yuan-etal-2017-machine,
    title = "Machine Comprehension by Text-to-Text Neural Question Generation",
    author = "Yuan, Xingdi  and
      Wang, Tong  and
      Gulcehre, Caglar  and
      Sordoni, Alessandro  and
      Bachman, Philip  and
      Zhang, Saizheng  and
      Subramanian, Sandeep  and
      Trischler, Adam",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2603",
    doi = "10.18653/v1/W17-2603",
    pages = "15--25",
}
@inproceedings{wang-etal-2017-emergent,
    title = "Emergent Predication Structure in Hidden State Vectors of Neural Readers",
    author = "Wang, Hai  and
      Onishi, Takeshi  and
      Gimpel, Kevin  and
      McAllester, David",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2604",
    doi = "10.18653/v1/W17-2604",
    pages = "26--36",
}
@inproceedings{cheri-bhattacharyya-2017-towards,
    title = "Towards Harnessing Memory Networks for Coreference Resolution",
    author = "Cheri, Joe  and
      Bhattacharyya, Pushpak",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2605",
    doi = "10.18653/v1/W17-2605",
    pages = "37--42",
}
@inproceedings{liang-etal-2017-combining,
    title = "Combining Word-Level and Character-Level Representations for Relation Classification of Informal Text",
    author = "Liang, Dongyun  and
      Xu, Weiran  and
      Zhao, Yinge",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2606",
    doi = "10.18653/v1/W17-2606",
    pages = "43--47",
}
@inproceedings{fan-etal-2017-transfer,
    title = "Transfer Learning for Neural Semantic Parsing",
    author = "Fan, Xing  and
      Monti, Emilio  and
      Mathias, Lambert  and
      Dreyer, Markus",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2607",
    doi = "10.18653/v1/W17-2607",
    pages = "48--56",
}
@inproceedings{shen-etal-2017-modeling,
    title = "Modeling Large-Scale Structured Relationships with Shared Memory for Knowledge Base Completion",
    author = "Shen, Yelong  and
      Huang, Po-Sen  and
      Chang, Ming-Wei  and
      Gao, Jianfeng",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2608",
    doi = "10.18653/v1/W17-2608",
    pages = "57--68",
}
@inproceedings{kadlec-etal-2017-knowledge,
    title = "Knowledge Base Completion: Baselines Strike Back",
    author = "Kadlec, Rudolf  and
      Bajgar, Ondrej  and
      Kleindienst, Jan",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2609",
    doi = "10.18653/v1/W17-2609",
    pages = "69--74",
}
@inproceedings{brarda-etal-2017-sequential,
    title = "Sequential Attention: A Context-Aware Alignment Function for Machine Reading",
    author = "Brarda, Sebastian  and
      Yeres, Philip  and
      Bowman, Samuel",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2610",
    doi = "10.18653/v1/W17-2610",
    pages = "75--80",
}
@inproceedings{rygl-etal-2017-semantic,
    title = "Semantic Vector Encoding and Similarity Search Using Fulltext Search Engines",
    author = "Rygl, Jan  and
      Pomik{\'a}lek, Jan  and
      {\v{R}}eh{\r{u}}{\v{r}}ek, Radim  and
      R{\r{u}}{\v{z}}i{\v{c}}ka, Michal  and
      Novotn{\'y}, V{\'\i}t  and
      Sojka, Petr",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2611",
    doi = "10.18653/v1/W17-2611",
    pages = "81--90",
}
@inproceedings{peng-dredze-2017-multi,
    title = "Multi-task Domain Adaptation for Sequence Tagging",
    author = "Peng, Nanyun  and
      Dredze, Mark",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2612",
    doi = "10.18653/v1/W17-2612",
    pages = "91--100",
}
@inproceedings{upadhyay-etal-2017-beyond,
    title = "Beyond Bilingual: Multi-sense Word Embeddings using Multilingual Context",
    author = "Upadhyay, Shyam  and
      Chang, Kai-Wei  and
      Taddy, Matt  and
      Kalai, Adam  and
      Zou, James",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2613",
    doi = "10.18653/v1/W17-2613",
    pages = "101--110",
}
@inproceedings{chen-etal-2017-doctag2vec,
    title = "{D}oc{T}ag2{V}ec: An Embedding Based Multi-label Learning Approach for Document Tagging",
    author = "Chen, Sheng  and
      Soni, Akshay  and
      Pappu, Aasish  and
      Mehdad, Yashar",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2614",
    doi = "10.18653/v1/W17-2614",
    pages = "111--120",
}
@inproceedings{grzegorczyk-kurdziel-2017-binary,
    title = "Binary Paragraph Vectors",
    author = "Grzegorczyk, Karol  and
      Kurdziel, Marcin",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2615",
    doi = "10.18653/v1/W17-2615",
    pages = "121--130",
}
@inproceedings{moirangthem-etal-2017-representing,
    title = "Representing Compositionality based on Multiple Timescales Gated Recurrent Neural Networks with Adaptive Temporal Hierarchy for Character-Level Language Models",
    author = "Moirangthem, Dennis Singh  and
      Son, Jegyung  and
      Lee, Minho",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2616",
    doi = "10.18653/v1/W17-2616",
    pages = "131--138",
}
@inproceedings{madhyastha-espana-bonet-2017-learning,
    title = "Learning Bilingual Projections of Embeddings for Vocabulary Expansion in Machine Translation",
    author = "Madhyastha, Pranava Swaroop  and
      Espa{\~n}a-Bonet, Cristina",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2617",
    doi = "10.18653/v1/W17-2617",
    pages = "139--145",
}
@inproceedings{botschen-etal-2017-prediction,
    title = "Prediction of Frame-to-Frame Relations in the {F}rame{N}et Hierarchy with Frame Embeddings",
    author = "Botschen, Teresa  and
      Mousselly-Sergieh, Hatem  and
      Gurevych, Iryna",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2618",
    doi = "10.18653/v1/W17-2618",
    pages = "146--156",
}
@inproceedings{schwenk-douze-2017-learning,
    title = "Learning Joint Multilingual Sentence Representations with Neural Machine Translation",
    author = "Schwenk, Holger  and
      Douze, Matthijs",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2619",
    doi = "10.18653/v1/W17-2619",
    pages = "157--167",
}
@inproceedings{kunze-etal-2017-transfer,
    title = "Transfer Learning for Speech Recognition on a Budget",
    author = "Kunze, Julius  and
      Kirsch, Louis  and
      Kurenkov, Ilia  and
      Krug, Andreas  and
      Johannsmeier, Jens  and
      Stober, Sebastian",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2620",
    doi = "10.18653/v1/W17-2620",
    pages = "168--177",
}
@inproceedings{asaadi-rudolph-2017-gradual,
    title = "Gradual Learning of Matrix-Space Models of Language for Sentiment Analysis",
    author = "Asaadi, Shima  and
      Rudolph, Sebastian",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2621",
    doi = "10.18653/v1/W17-2621",
    pages = "178--185",
}
@inproceedings{godin-etal-2017-improving,
    title = "Improving Language Modeling using Densely Connected Recurrent Neural Networks",
    author = "Godin, Fr{\'e}deric  and
      Dambre, Joni  and
      De Neve, Wesley",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2622",
    doi = "10.18653/v1/W17-2622",
    pages = "186--190",
}
@inproceedings{trischler-etal-2017-newsqa,
    title = "{N}ews{QA}: A Machine Comprehension Dataset",
    author = "Trischler, Adam  and
      Wang, Tong  and
      Yuan, Xingdi  and
      Harris, Justin  and
      Sordoni, Alessandro  and
      Bachman, Philip  and
      Suleman, Kaheer",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2623",
    doi = "10.18653/v1/W17-2623",
    pages = "191--200",
}
@inproceedings{phillips-etal-2017-intrinsic,
    title = "Intrinsic and Extrinsic Evaluation of Spatiotemporal Text Representations in Twitter Streams",
    author = "Phillips, Lawrence  and
      Shaffer, Kyle  and
      Arendt, Dustin  and
      Hodas, Nathan  and
      Volkova, Svitlana",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2624",
    doi = "10.18653/v1/W17-2624",
    pages = "201--210",
}
@inproceedings{tang-etal-2017-rethinking,
    title = "Rethinking Skip-thought: A Neighborhood based Approach",
    author = "Tang, Shuai  and
      Jin, Hailin  and
      Fang, Chen  and
      Wang, Zhaowen  and
      de Sa, Virginia",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2625",
    doi = "10.18653/v1/W17-2625",
    pages = "211--218",
}
@inproceedings{schulz-etal-2017-frame,
    title = "A Frame Tracking Model for Memory-Enhanced Dialogue Systems",
    author = "Schulz, Hannes  and
      Zumer, Jeremie  and
      El Asri, Layla  and
      Sharma, Shikhar",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2626",
    doi = "10.18653/v1/W17-2626",
    pages = "219--227",
}
@inproceedings{gulcehre-etal-2017-plan,
    title = "Plan, Attend, Generate: Character-Level Neural Machine Translation with Planning",
    author = "Gulcehre, Caglar  and
      Dutil, Francis  and
      Trischler, Adam  and
      Bengio, Yoshua",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2627",
    doi = "10.18653/v1/W17-2627",
    pages = "228--234",
}
@inproceedings{michel-etal-2017-geometry,
    title = "Does the Geometry of Word Embeddings Help Document Classification? A Case Study on Persistent Homology-Based Representations",
    author = "Michel, Paul  and
      Ravichander, Abhilasha  and
      Rijhwani, Shruti",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2628",
    doi = "10.18653/v1/W17-2628",
    pages = "235--240",
}
@inproceedings{subramanian-etal-2017-adversarial,
    title = "Adversarial Generation of Natural Language",
    author = "Subramanian, Sandeep  and
      Rajeswar, Sai  and
      Dutil, Francis  and
      Pal, Chris  and
      Courville, Aaron",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2629",
    doi = "10.18653/v1/W17-2629",
    pages = "241--251",
}
@inproceedings{shen-etal-2017-deep,
    title = "Deep Active Learning for Named Entity Recognition",
    author = "Shen, Yanyao  and
      Yun, Hyokun  and
      Lipton, Zachary  and
      Kronrod, Yakov  and
      Anandkumar, Animashree",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2630",
    doi = "10.18653/v1/W17-2630",
    pages = "252--256",
}
@inproceedings{johansen-socher-2017-learning,
    title = "Learning when to skim and when to read",
    author = "Johansen, Alexander  and
      Socher, Richard",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2631",
    doi = "10.18653/v1/W17-2631",
    pages = "257--264",
}
@inproceedings{tu-etal-2017-learning,
    title = "Learning to Embed Words in Context for Syntactic Tasks",
    author = "Tu, Lifu  and
      Gimpel, Kevin  and
      Livescu, Karen",
    booktitle = "Proceedings of the 2nd Workshop on Representation Learning for {NLP}",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/W17-2632",
    doi = "10.18653/v1/W17-2632",
    pages = "265--275",
}

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}

h1, h4{
    line-height: 2;
    margin: 0;
}

.col-md-3, .col-md-12{
    padding: 0;
}

.fast_food_content{
    padding-left: 10%;
    font-size: 18px;
    color: rgba(0,0,0,.8);
}

.fast_food_content p{
    font-weight: 300;
    font-size: 19px;
}

#fast-foods-drink{
    text-align: right;
}

#fast-foods-drinks .img-thumbnail img:first-child{
    margin-top: 15px;
}

#fast-foods-drinks .img-thumbnail img:last-child{
    margin-bottom: 15px;
}

#fast-foods-drink .img-thumbnail img{
    margin-top: 15px;
}

#fast-foods-drink .img-thumbnail img{
    margin-bottom: 15px;
    width: 50%;
}

#fast-foods-drink .img-thumbnail {
    padding: 20px;
}

button[type=button]{
    background-color: unset;
    border: 1px solid #e75937;
    color: #e75937;
    font-weight: 300;
    text-transform: uppercase;
}

.fast-foods{
    width: 80%;
    height: 600px;
    margin: auto;
    padding-top: 7%;
    position: relative;
}

.menu-tabs{
    background-color: #fff;
    height: 13%;
    color: rgba(0,0,0,.7);
    overflow: hidden;
}

.nav-tabs{
    text-align: center;
    height: 100%;
    background: rgb(211, 211, 211);
}

#menu-list {
    height: 600px;
}

#menu-list a{
    height: 100%;
    font-size: 21px;
    font-weight: 500;
    padding-top: 15px;

}

#menu-list a:active{
    border: none;
    background-color: #fff;
    color: #e75937;
}
#menu-list .nav-item{

}

.active{
    border: none;
    background-color: #fff;
    color: #e75937;
}

.nav-link:hover{
    border-color: white white white !important;
    color: #e75937;
    background-color: ;
}

.nav-item:hover{
    cursor: pointer;
    border: none;
    color: #e75937;
}

.menu-tabs .row{
    height: 100%;
}

.tab-items {
    height: 330px;
    background-color: #fff;
    margin-left: 0px;
    overflow: hidden;
    padding: 30px 0 0 0px;
    align-items: end;
    justify-content: space-evenly;
    display: none;
}

.fast-foods .panel{
    text-align: center;
}

#fast-foods-drinks .img-thumbnail{
    padding: 5px 15px 15px 15px;
}

.panel p {
    padding: 15px;
    font-size: 16px;
    color: rgb(231, 89, 55);
    font-weight: 800;
    letter-spacing: 0.5px;
}

.chevron{
    position: absolute;
    height: 30px;
    transform: translate(1%, -64%);
    top: 50%;
    cursor: pointer;
}

.chevron-1{
    left: 3%;
}

.chevron-2{
    right: 2.3%;
}

.newsletter{
    background: url('../assets/backgrounds/subscribe.jpg') center center/cover;
    padding: 100px 0;
}

.display{
    display: inline-block;
}

.item {
    height: 16rem;
    width: 16rem;
}

.owl-carousel:first-child {
    padding-left: 5%;
}

.owl-item{
    display: inline-block;
}

.owl-carousel{
    width: 100%;
}

button[role=presentation] {
    border: none;
    position: absolute;
    font-size: 45px;
    cursor: pointer;
}

button[role=presentation]:hover{
    color: #e75937;
    opacity: .5;
}

.owl-prev{
    top:30%;
    left: 2%;
}

.owl-next{
    top:30%;
    right: 2%;
}

.owl-dot{
    display: none;
}

.card{
    border: none;
}

.owl-carousel .card-title {
    margin-bottom: .75rem;
    text-align: center;
    font-size: 15px;
    font-weight: bolder;
    letter-spacing: 1px;
}

.owl-theme .owl-nav.disabled+.owl-dots {
    margin: 0 0 0 -92px !important;
}

.width{
    width: 79%;
    margin: auto;
    margin-bottom: 15px;
}

.testimonials h4{
    color: #e75937;
    font-size: 20px;
}

.testimonials h6 {
    font-size: 1.6rem;
}

.newsletter .container{
    width: 54%;
    margin: auto;
    text-align: center;
}

.newsletter .form-group{
    width: 60%;
}

#inputEmail{
    width: 100%;
    height: 45px;
}

.newsletter button{
    width: 35%;
    height: 45px;
}

.form-inline input,
.form-inline button{
    font-size: 15px;
}

.form-inline input{
    background-color: rgba(255, 255, 255, .2);
    border: none;
    padding: 5px 30px;
    color: #fff !important;
}

.form-inline input::placeholder{
    color: #fff;
}

.form-inline input:focus{
    color: #000 !important;
    letter-spacing: 1px;
}

.form-inline button{
    background-color: #e75937;
    border: none;
}

.footer{
    background-color: #e75937;
    color: #fff;
}

.footer h1,
.footer img{
    height: 45px;
    margin: 10px;
}

.footer .col-md-3{
    margin: auto;
    margin-left: 50%;
    transform: translateX(-25%);
}

.footer img{
    margin-top: 20px;
}

.footer .col-md-3 > p{
    margin: 10px 5px;
    letter-spacing: 1px;
    font-weight: 500;
    font-size: 20px;
}

.footer .row .row img{
    height: 55px;
    margin: 40px 10px;
}

.p-footer{
    font-size: 17px !important;
    font-weight: 300 !important;
    padding-left: 9px;
}

.testimonials .owl-item{
    width: 58px;
}

.testimonials .item{
    height: auto;
    width: 100%;
}

.testimonials .item img{
    height: auto;
}

.overflow_hidden{
    overflow: hidden;
}

.testimonials .owl-item{
    width: 58.932px !important;
}

.my-carousel{
    width: 100%;
    margin: auto;
    height: 100%;
    padding: 0;
    overflow: hidden;
}

.testimonials .my-carousel .active{
    color: #000;
}

.owl-stage{
    display: flex;
}

.my-carousel .owl-item{
    padding: 0 10px;
    width: 610px !important;
}

.testimonials .col-md-7{
    height: 250px;
}

.primary-button a {
    display: inline-block;
    background-color: #e75937;
    color: #fff;
    letter-spacing: 1px;
    font-size: 12px;
    padding: 12px 18px;
    font-weight: 600;
    text-decoration: none;
    text-transform: uppercase;
    border: 1px solid transparent;
}

.primary-button a:hover {
    background-color: transparent;
    color: #e75937;
    border: 1px solid #e75937;
    -moz-transition: all 0.2s linear;
    -o-transition: all 0.2s linear;
    -webkit-transition: all 0.2s linear;
}

/** media queries **/
@media screen and (max-width: 1256px){
    .newsletter button {
        width: 33%;
    }
}

@media screen and (max-width: 1200px){
    #fast-foods-drinks .img-thumbnail img{
        width: 400px;
        height: 195px;
    }

    #fast-foods-drink .img-thumbnail img{
        height: 370px;
    }

    .owl-carousel:first-child {
        padding-left: 6%;
    }
}

@media screen and (max-width: 1096px){
    .owl-carousel:first-child {
        padding-left: 3%;
    }
}

@media screen and (max-width: 1024px){
    .owl-carousel:first-child {
        padding-left: 8%;
    }

    .footer .col-md-3 {
        min-width: 35% !important;
    }
}

@media screen and (max-width: 992px){
    #fast-foods-drinks .img-thumbnail img {
        width: 290px;
        height: 180px;
    }

    #fast-foods-drinks .img-thumbnail {
        padding-left: 25px;
    }

    .jumbotron h1 {
        font-size: 58px;
    }

    .fast_food_content p {
        font-size: 15px;
    }

    #fast-foods-drink .img-thumbnail img {
        width: 50%;
        height: 350px;
    }

    #drinks {
        padding: 0 10% 0 0px;
    }

    .img-thumbnail {
        height: 400px;
    }

    #men {
        height: 150px;
    }

    .showcase {
        padding-bottom: 23px;
    }

    .newsletter .form-group {
        width: 100%;
        margin-left: 0 !important;
    }

    .newsletter button {
        width: 100%;
    }
}

@media screen and (max-width: 796px){

    .newsletter button {
        width: 100%;
    }

    .owl-carousel:first-child {
        padding-left: 4%;
    }
}

@media screen and (max-width: 768px){
    .footer .col-md-3{
        margin-left: 30%;
    }

    #fast-foods-drinks .img-thumbnail img {
        width: 425px;
    }

    .fast_food_content {
        margin-top: 50px;
    }

    #fast-foods-drink .img-thumbnail img {
        width: 250px;
    }

    .owl-carousel:first-child {
        padding-left: 7%;
    }

    #fast-foods-drink {
        text-align: left;
        display: block;
    }

    #fast-foods-drink .img-thumbnail img {
        width: 50%;
    }

    #fast-foods-drink .img-thumbnail:second-child {
        float: right;
    }

    #drinks {
        padding: 0 0% 0 10%;
    }

    #fast-foods-drink .fast_food_content{
        margin-bottom: 50px;
    }

    #menu-list a {
        font-size: 18px;
    }

    .owl-carousel:first-child {
        padding-left: 3%;
    }

    .fast-foods {
        padding-top: 14%;
    }

    .testimonials .col-md-7{
        margin-bottom: 50px;
    }

    .footer .col-md-3 {
        margin-left: 45%;
        width: 40%;
    }
}

@media screen and (max-width: 700px){
    .owl-carousel:first-child {
        padding-left: 25%;
    }

    #menu-list a {
        font-size: 17px;
    }
}

@media screen and (max-width: 600px){
    #men {
        height: 110px;
        font-size: 19px;
    }

    .owl-carousel:first-child {
        padding-left: 22%;
    }

    .owl-dots{
        margin-left: -108px;
    }
}

@media screen and (max-width: 576px){
    #men .col{
        padding: 0;
    }

    #fast-foods-drinks .img-thumbnail img {
        width: 445px;
    }

    .owl-carousel:first-child {
        padding-left: 18%;
    }

    .img-thumbnail {
        width: 555px;
    }

    #fast-foods-drink .img-thumbnail img {
        width: 50%;
    }

    #fast-foods-drink .img-thumbnail {
        padding-right: 20px;
        padding-left: 25px;
    }

    #menu-list a {
        font-size: 15px;
    }

    .showcase-header {
        font-size: 24px !important;
    }

    .footer .col-md-3 {
        margin-left: 40%;
        width: 50%;
    }

    #tab-1{
        padding-left: 10px;
    }

    .owl-dots {
        margin-left: -60px;
    }

    .owl-theme .owl-nav {
        margin-top: 0 !important;
    }

    .testimonials .col-md-7 {
        height: 300px;
    }
}

@media screen and (max-width: 500px){
    .owl-carousel:first-child {
        padding-left: 16%;
    }

    #fast-foods-drinks .img-thumbnail img {
        width: 415px;
    }

    #men {
        height: 90px;
        font-size: 18px;
    }

    .testimonials .col-md-7 {
        height: 380px;
    }

    .testimonials .col-md-5 {
        padding-left: 5px;
    }

    .testimonials {
        padding: 20px 0px 20px 5px;
    }
}

@media screen and (max-width: 460px){
    .owl-carousel:first-child {
        padding-left: 16%;
    }

    #fast-foods-drinks .img-thumbnail img {
        width: 380px;
    }

    .owl-theme .owl-nav.disabled+.owl-dots {
        margin: 0 0 0 -60px !important;
    }

    .testimonials {
        margin: 75px 50px 75px 50px;
    }

    .newsletter .container {
        width: 80%;
    }

    .footer .col-md-3 {
        margin-left: 43%;
        width: 60%;
    }
}

@media screen and (max-width: 420px){
    #fast-foods-drinks .img-thumbnail img {
        max-width: 345px;
    }

    .fast_food_content {
        padding-right: 10%;
    }
}

@media screen and (max-width: 400px){
    #fast-foods-drinks .img-thumbnail img {
        max-width: 330px;
    }

    .owl-theme .owl-nav.disabled+.owl-dots {
        margin: 0 0 0 -30px !important;
    }

    #fast-foods-drinks .img-thumbnail img {
        max-width: 315px;
    }

    .owl-carousel:first-child {
        padding-left: 10%;
    }

    .img-1 p, .img-2 p, .img-3 p {
        margin-top: 35%;
    }

    .jumbotron h1 {
        font-size: 40px;
    }

    .footer .col-md-3 {
        margin-left: 35%;
    }
}

@media screen and (max-width: 380px){
    .footer .col-md-3 {
        width: 70%;
    }

    .party, .happy {
        font-size: 15px;
    }

    #fast-foods-drinks .img-thumbnail img {
        max-width: 310px;
    }

    .owl-carousel:first-child {
        padding-left: 7%;
    }

    .testimonials {
        margin: 75px 30px 75px 30px;
    }

    .owl-dots {
        margin-left: -15px;
    }

    #fast-foods-drinks .img-thumbnail img {
        max-width: 290px;
    }

    .owl-theme .owl-nav.disabled+.owl-dots {
        margin: 0 0 0 -30px !important;
    }
}

@media screen and (max-width: 360px){
    #fast-foods-drinks .img-thumbnail img {
        max-width: 275px;
    }

    .fast-foods {
        width: 90%;
    }

    .owl-carousel:first-child {
        padding-left: 9%;
    }
}

@media screen and (max-width: 350px){
    #fast-foods-drinks .img-thumbnail img {
        max-width: 265px;
    }

    .owl-carousel .owl-item img {
        width: 95% !important;
    }
}

@media screen and (max-width: 340px){
    #fast-foods-drinks .img-thumbnail img {
        max-width: 260px;
    }

    .footer .col-md-3 {
        width: 80%;
    }
}

@media screen and (max-width: 320px){
    #fast-foods-drinks .img-thumbnail img {
        max-width: 240px;
    }

    #men {
        height: 90px;
        font-size: 16px;
    }
}

license: MIT

repository: JosephMasaka/anitaskitchen-master

repo_name: JosephMasaka/anitaskitchen-master

extension: css


text:
@BOOK{Encyclopedia,
  title        = {Художественная энциклопедия зарубежного классического искусства},
  publisher    = {Большая Рос. энцикл.},
  year         = {1996},
  address      = {М.},
  note         = {1 электрон. опт. диск (CD-ROM)},
  language     = {russian},
  media        = {eresource},
}


text:
@article{anon:sort-scan-debitcredit-bench:1985,
  author = "{Anon, et. al.}",
  title = {A measure of transaction processing power},
  journal = {Datamation},
  volume = {31},
  number = {7},
  year = {1985},
  issn = {0011-6963},
  pages = {112--118},
  publisher = {Cahners Publishing Company},
  address = {Newton, MA, USA},
  note = {Available at \url{http://sortbenchmark.org/AMeasureOfTransactionProcessingPower.doc} accessed June 2009}
}

repository: dataseries/Lintel

repo_name: dataseries/Lintel

gha_language: Perl


text:
@inproceedings{Sanchez-Monedero2017imibic,
 author = {J. Sánchez-Monedero and M. Pérez-Ortiz and A. Sáez and P. A. Gutiérrez and C. Hervás-Martínez},
 booktitle = {8th IMIBIC Younh Investigators Meeting},
 owner = {javi},
 timestamp = {2018.02.19},
 title = {Advanced feature extraction and machine learning models to melanoma and Breslow index detection},
 year = {2017}
}

repository: javism/academic-kickstart

repo_name: javism/academic-kickstart

gha_license_id: MIT


text:
@Article{biecek2003zastosowanie,
  title = {Zastosowanie zagadnienia jednoczesnego testowania wielu hipotez w badaniach genetycznych},
  author = {Przemys{\l}aw Biecek},
  journal = {Praca magisterska},
  year = {2003},
}


text:
.lBody {
  background: #ccc;
  height: 740px;
  margin: 4px auto;
  /* max-height: calc(100vh - 8px); */
  width: 375px;
}

.lWrapper {
  background: #fff;
  border-radius: 4px 4px 4px 4px;
  display: flex;
  flex-direction: column;
  height: 100%;
}

.lHeader {
  background: #44c45e;
  border-radius: 4px 4px 0 0;
  flex: 0 0 auto;
  padding: 15px;
}

.lContent {
  flex: 1 1 auto;
  padding: 15px;
}

.lFooter {
  border-top: 1px solid #ddd;
  flex: 0 0 auto;
}

.lFooter.login {
  border-top: none;
}

.logo {
  margin-top: 50px;
  text-align: center;
}

.logo img {
  height: 100px;
}

.atthetop {
  margin-top: 50px;
}

.divider {
  margin: 2em 0;
  position: relative;
  text-align: center;
}

.divider::before {
  content: '';
  display: block;
  position: absolute;
  top: 50%;
  border-top: 1px solid #ddd;
  width: 100%;
}

.divider span {
  background: #fff;
  padding: 4px;
  position: relative;
}

.icon {
  width: 16px;
}

.tag {
  width: 12px;
}

.tag img {
  fill: #ddd;
}

.sso {
  position: relative;
}

.sso img {
  left: 8px;
  position: absolute;
  top: 8px;
}

.nav-pills > li.active > a,
.nav-pills > li.active > a:focus,
.nav-pills > li.active > a:hover {
  background: #44c45e;
}

.nav-pills > li > a {
  border-radius: 0 0 4px 4px;
}

.nav-pills > li:first-child > a {
  border-radius: 0 0 0 4px;
}

.nav-pills > li:last-child > a {
  border-radius: 0 0 4px 0;
}

.centered {
  text-align: center;
}

.profile {
  position: relative;
  text-align: center;
}

.edit {
  position: absolute;
  right: 0;
  top: 0;
}

.profile .avatar {
  border: 3px solid #fff;
  border-radius: 50%;
  box-shadow: 1px 1px 5px 0 #00000099;
  display: inline-block;
  margin: 15px auto 0;
  height: 150px;
  overflow: hidden;
  width: 150px;
}

.profile .name {
  font-size: 24px;
}

.profile label {
  margin-bottom: 0;
}

.profile .form-group {
  margin-top: 1em;
}

.profile .details {
  background: #dddddd66;
  margin: 0 -15px;
  padding: 1px 15px;
  text-align: left;
}

.areasofinterest span,
.skills span {
  color: #337ab7;
  cursor: pointer;
}

.project-list {
  border-top: 1px solid #ddd;
}

.project {
  border-bottom: 1px solid #ddd;
  cursor: pointer;
  margin-bottom: 4px;
  padding: 4px;
}

.project .badge {
  float: right;
}

.projects,
.project-details {
  padding-top: 1px;
  position: relative;
}

.collaborator-heading {
  clear: both;
  line-height: 34px;
  position: relative;
}

.collaborator-heading .badge {
  vertical-align: initial;
  margin-left: 100px;
  position: absolute;
  left: 97px;
  top: 9px;
}

.controls {
  float: right;
}

.controls .btn {
  border: none;
  border-radius: 50%;
  padding: 6px;
  width: 34px;
}

.project-details .details {
  background: #dddddd66;
  margin: 0 -15px;
  padding: 15px;
}

repository: moonray/research-collaborators

repo_name: moonray/research-collaborators


text:
@article{torrens2006photoluminescence,
 author = {Torrens, ON and Milkie, DE and Zheng, M and Kikkawa, JM},
 journal = {Nano letters},
 number = {12},
 pages = {2864--2867},
 publisher = {ACS Publications},
 title = {Photoluminescence from intertube carrier migration in single-walled carbon nanotube bundles},
 volume = {6},
 year = {2006}
}

repository: dmilkie/starter-academic

repo_name: dmilkie/starter-academic


text:
@article{geng2019few-shot,
  author    = {Ruiying Geng and Binhua Li and Yongbin Li and Yuxiao Ye and Ping Jian and Jian Sun},
  title     = {Few-Shot Text Classification with Induction Network},
  journal   = {CoRR},
  volume    = {abs/1902.10482},
  year      = {2019},
  url       = {http://arxiv.org/abs/1902.10482}
}

url: https://raw.githubusercontent.com/Hugh-Shi/DL-NLP-Readings/924e4d189e5660c5b5d4854278f3df755ae2231d/Bibtex/Few-Shot Text Classification with Induction Network.bib

repository: Hugh-Shi/DL-NLP-Readings

repo_name: Hugh-Shi/DL-NLP-Readings


text:
/* columns.css */

body {
    width:100%;
    height:100%;
    margin: 0;
    padding:0;
}

.main {
    width:100%;
    height:100%;
    margin:0;
    padding:0;

}

.scene {
    width:80%;
    margin:50px auto;
    background-color:#999;
}

.subscene {

}

.block {

}

.subpx {

}

repository: bFraley/greatdivide

repo_name: bFraley/greatdivide


text:
.popup {
    position: fixed;
    border-radius: var(--radius-popup-border);
    background-color: var(--color-foreground);
    filter: drop-shadow(0 0 var(--radius-blur-shadow) var(--color-shadow));
    max-width: calc(100vw - 2 * var(--spacing-large));

    --height-tip: 10px;
    --width-tip: 20px;

    .tip {
        position: absolute;
        top: unset;
        right: unset;
        bottom: unset;
        left: unset;
        background-color: #fff;
        width: var(--width-tip);
        height: var(--height-tip);
    }

    &.top {
        .tip {
            bottom: calc(-1 * var(--height-tip));
            clip-path: polygon(100% 0%, 0 0, 50% 100%);
        }
    }

    &.bottom {
        .tip {
            top: calc(-1 * var(--height-tip));
            clip-path: polygon(50% 0%, 0% 100%, 100% 100%);
        }
    }

    &.left {
        .tip {
            right: var(--width-tip);
        }
    }

    &.right {
        .tip {
            left: var(--width-tip);
        }
    }

    .content {
        width: 100%;
        height: 100%;
        overflow: auto;
    }
}

repository: mapswipe/python-mapswipe-workers

repo_name: mapswipe/python-mapswipe-workers

gha_language: TypeScript


text:
@article{2007ApJ...666.1116S,
 abstract = {We report the discovery and early observations of the peculiar Type IIn
supernova (SN) 2006gy in NGC 1260. With a peak visual magnitude
of about -22, it is the most luminous supernova ever recorded.
Its very slow rise to maximum took
åisebox-0.5ex~70 days, and it stayed brighter
than -21 mag for about 100 days. It is not yet clear what powers
the enormous luminosity and the total radiated energy of
\i̊sebox-0.5ex~10$^51$ erg, but we argue
that any known mechanism-thermal emission, circumstellar
interaction, or $^56$Ni decay-requires a very massive
progenitor star. The circumstellar interaction hypothesis would
require truly exceptional conditions around the star, which, in
the decades before its death, must have experienced a luminous
blue variable (LBV) eruption like the 19th century eruption of
\ensuremathη Carinae. However, this scenario fails to
explain the weak and unabsorbed soft X-rays detected by Chandra.
Radioactive decay of $^56$Ni may be a less objectionable
hypothesis, but it would imply a large Ni mass of
\rs̊ebox-0.5ex~22 M$_solar$, requiring SN
2006gy to have been a pair-instability supernova where the
star's core was obliterated. While this is still uncertain, SN
2006gy is the first supernova for which we have good reason to
suspect a pair-instability explosion. Based on a number of lines
of evidence, we eliminate the hypothesis that SN 2006gy was a
``Type IIa'' event, that is, a white dwarf exploding inside a
hydrogen envelope. Instead, we propose that the progenitor was a
very massive evolved object like \ensuremathη Carinae
that, contrary to expectations, failed to shed its hydrogen
envelope. SN 2006gy implies that some of the most massive stars
can explode prematurely during the LBV phase, never becoming
Wolf-Rayet stars. SN 2006gy also suggests that they can create
brilliant supernovae instead of experiencing ignominious deaths
through direct collapse to a black hole. If such a fate is
common among the most massive stars, then observable supernovae
from Population III stars in the early universe will be more
numerous than previously believed.},
 adsnote = {Provided by the SAO/NASA Astrophysics Data System},
 adsurl = {https://ui.adsabs.harvard.edu/abs/2007ApJ...666.1116S},
 archiveprefix = {arXiv},
 author = {Smith, Nathan and Li, Weidong and Foley, Ryan J. and
Wheeler, J. Craig and Pooley, David and Chornock, Ryan and
Filippenko, Alexei V. and Silverman, Jeffrey M. and
Quimby, Robert and Bloom, Joshua S. and Hansen, Charles},
 doi = {10.1086/519949},
 eprint = {astro-ph/0612617},
 journal = {\apj},
 keywords = {Stars: Circumstellar Matter, Stars: Evolution, supernovae: individual (SN 2006gy), Astrophysics},
 month = {Sep},
 number = {2},
 pages = {1116-1128},
 primaryclass = {astro-ph},
 title = {SN 2006gy: Discovery of the Most Luminous Supernova Ever Recorded, Powered by the Death of an Extremely Massive Star like \ensuremathη Carinae},
 volume = {666},
 year = {2007}
}

repository: profjsb/my-content

repo_name: profjsb/my-content


text:
@INPROCEEDINGS{Chaudhuri2009,
  author = {Abon Chaudhuri and Han-Wei Shen},
  title = {A Self-adaptive Treemap-based Technique for Visualizing Hierarchical Data in {3D}},
  pages = {105--112},
  abstract = {In this paper, we present a novel adaptive visualization technique where the constituting polygons dynamically change their geometry and other visual attributes depending on user interaction. These changes take place with the objective of conveying required level of detail to the user through each view. Our proposed technique is successfully applied to build a treemap-based but 3D visualization of hierarchical data, a widely used information structure. This new visualization exploits its adaptive nature to address issues like cluttered display, imperceptible hierarchy, lack of smooth zoom-in and out technique which are common in tree visualization. We also present an algorithm which utilizes the flexibility of our proposed technique to deal with occlusion, a problem inherent in any 3D information visualization. On one hand, our work establishes adaptive visualization as a means of displaying tree-structured data in 3D. On the other, it promotes the technique as a potential candidate for being employed to visualize other information structures also.},
  doi = {10.1109/PACIFICVIS.2009.4906844},
  year = {2009},
  booktitle = {PacificVis'09: Proceedings of the IEEE Pacific Visualization Symposium},
  editor = {Peter Eades and Thomas Ertl and Han-Wei Shen},
  publisher = {IEEE Computer Society},
  isbn = {9781424444055}
}

repository: vis-au/treevisnet

repo_name: vis-au/treevisnet


text:
@article{PhysRevE87013308,
  title = {Information field dynamics for simulation scheme construction},
  author = {En\ss{}lin, Torsten A.},
  journal = {Phys. Rev. E},
  volume = {87},
  issue = {1},
  pages = {013308},
  numpages = {17},
  year = {2013},
  month = {Jan},
  publisher = {American Physical Society},
  doi = {10.1103/PhysRevE.87.013308},
  link = {https://link.aps.org/doi/10.1103/PhysRevE.87.013308},
  abstract = {Information field dynamics (IFD) is introduced here as a framework to derive numerical schemes for the simulation of physical and other fields without assuming a particular subgrid structure as many schemes do. IFD constructs an ensemble of nonparametric subgrid field configurations from the combination of the data in computer memory, representing constraints on possible field configurations, and prior assumptions on the subgrid field statistics. Each of these field configurations can formally be evolved to a later moment since any differential operator of the dynamics can act on fields living in continuous space. However, these virtually evolved fields need again a representation by data in computer memory. The maximum entropy principle of information theory guides the construction of updated data sets via entropic matching, optimally representing these field configurations at the later time. The field dynamics thereby become represented by a finite set of evolution equations for the data that can be solved numerically. The subgrid dynamics is thereby treated within auxiliary analytic considerations. The resulting scheme acts solely on the data space. It should provide a more accurate description of the physical field dynamics than simulation schemes constructed ad hoc, due to the more rigorous accounting of subgrid physics and the space discretization process. Assimilation of measurement data into an IFD simulation is conceptually straightforward since measurement and simulation data can just be merged. The IFD approach is illustrated using the example of a coarsely discretized representation of a thermally excited classical Klein-Gordon field. This should pave the way towards the construction of schemes for more complex systems like turbulent hydrodynamics.}
}

@article{owhadi2015bayesian,
  title={Bayesian Numerical Homogenization},
  author={Owhadi, Houman},
  journal={Multiscale Modeling \& Simulation},
  volume={13},
  number={3},
  pages={812--828},
  year={2015},
  publisher={SIAM},
  link = {http://arxiv.org/abs/1406.6668},
  file = {http://arxiv.org/pdf/1406.6668v2.pdf},
  abstract = {Numerical homogenization, i.e. the finite-dimensional approximation of solution spaces of PDEs with arbitrary rough coefficients, requires the identification of accurate basis elements. These basis elements are oftentimes found after a laborious process of scientific investigation and plain guesswork. Can this identification problem be facilitated? Is there a general recipe/decision framework for guiding the design of basis elements? We suggest that the answer to the above questions could be positive based on the reformulation of numerical homogenization as a Bayesian Inference problem in which a given PDE with rough coefficients (or multi-scale operator) is excited with noise (random right hand side/source term) and one tries to estimate the value of the solution at a given point based on a finite number of observations. We apply this reformulation to the identification of bases for the numerical homogenization of arbitrary integro-differential equations and show that these bases have optimal recovery properties. In particular we show how Rough Polyharmonic Splines can be re-discovered as the optimal solution of a Gaussian filtering problem.}
}

@article{conrad_probability_2015,
  title = {Probability {Measures} for {Numerical} {Solutions} of {Differential} {Equations}},
  file = {http://arxiv.org/pdf/1506.04592v1.pdf},
  link = {http://warwick.ac.uk/pints},
  abstract = {In this paper, we present a formal quantification of epistemic uncertainty induced by numerical solutions of ordinary and partial differential equation models. Numerical solutions of differential equations contain inherent uncertainties due to the finite dimensional approximation of an unknown and implicitly defined function. When statistically analysing models based on differential equations describing physical, or other naturally occurring, phenomena, it is therefore important to explicitly account for the uncertainty introduced by the numerical method. This enables objective determination of its importance relative to other uncertainties, such as those caused by data contaminated with noise or model error induced by missing physical or inadequate descriptors. To this end we show that a wide variety of existing solvers can be randomised, inducing a probability measure over the solutions of such differential equations. These measures exhibit contraction to a Dirac measure around the true unknown solution, where the rates of convergence are consistent with the underlying deterministic numerical method. Ordinary differential equations and elliptic partial differential equations are used to illustrate the approach to quantifying uncertainty in both the statistical analysis of the forward and inverse problems.},
  urldate = {2015-06-16},
  journal = {arXiv:1506.04592 [stat]},
  author = {Conrad, Patrick R. and Girolami, Mark and Särkkä, Simo and Stuart, Andrew and Zygalakis, Konstantinos},
  month = jun,
  year = {2015},
  note = {arXiv: 1506.04592},
  keywords = {Statistics - Methodology}
}

@article{oates_bayesian_2017,
  title = {Bayesian {Probabilistic} {Numerical} {Methods} for {Industrial} {Process} {Monitoring}},
  url = {http://arxiv.org/abs/1707.06107},
  abstract = {The use of high-power industrial equipment, such as large-scale mixing equipment or a hydrocyclone for separation of particles in liquid suspension, demands careful monitoring to ensure correct operation. The task of monitoring the liquid suspension can be posed as a time-evolving inverse problem and solved with Bayesian statistical methods. In this paper, we extend Bayesian methods to incorporate statistical models for the error that is incurred in the numerical solution of the physical governing equations. This enables full uncertainty quantification within a principled computation-precision trade-off, in contrast to the over-confident inferences that are obtained when numerical error is ignored. The method is cast with a sequential Monte Carlo framework and an optimised implementation is provided in Python.},
  urldate = {2017-07-20},
  journal = {arXiv:1707.06107 [stat]},
  author = {Oates, Chris J. and Cockayne, Jon and Aykroyd, Robert G.},
  month = jul,
  year = {2017},
  note = {arXiv: 1707.06107},
  keywords = {Statistics - Applications},
  file = {https://arxiv.org/pdf/1707.06107.pdf}
}

@article{2015arXiv150303467O,
   author = {{Owhadi}, H.},
    title = {Multigrid with rough coefficients and Multiresolution operator decomposition from Hierarchical Information Games},
  journal = {ArXiv},
  volume = {math.NA},
   issue = {1503.03467},
     year = 2015,
    month = mar,
    link = {http://arxiv.org/abs/1503.03467},
    file = {http://arxiv.org/pdf/1503.03467v4.pdf},
    abstract = {We introduce a near-linear complexity (geometric and meshless/algebraic) multigrid/multiresolution method for PDEs with rough ($L^\infty$) coefficients with rigorous a-priori accuracy and performance estimates. The method is discovered through a decision/game theory formulation of the problems of (1) identifying restriction and interpolation operators (2) recovering a signal from incomplete measurements based on norm constraints on its image under a linear operator (3) gambling on the value of the solution of the PDE based on a hierarchy of nested measurements of its solution or source term. The resulting elementary gambles form a hierarchy of (deterministic) basis functions of $H^1_0(\Omega)$ (gamblets) that (1) are orthogonal across subscales/subbands with respect to the scalar product induced by the energy norm of the PDE (2) enable sparse compression of the solution space in $H^1_0(\Omega)$ (3) induce an orthogonal multiresolution operator decomposition. The operating diagram of the multigrid method is that of an inverted pyramid in which gamblets are computed locally (by virtue of their exponential decay), hierarchically (from fine to coarse scales) and the PDE is decomposed into a hierarchy of independent linear systems with uniformly bounded condition numbers. The resulting algorithm is parallelizable both in space (via localization) and in bandwith/subscale (subscales can be computed independently from each other). Although the method is deterministic it has a natural Bayesian interpretation under the measure of probability emerging (as a mixed strategy) from the information game formulation and multiresolution approximations form a martingale with respect to the filtration induced by the hierarchy of nested measurements.}
}

@article{2016arXiv160507811C,
   author = {{Cockayne}, J. and {Oates}, C. and {Sullivan}, T. and {Girolami}, M.},
    title = {Probabilistic Meshless Methods for Partial Differential Equations and {B}ayesian Inverse Problems},
  journal = {ArXiv},
   issue = {1605.07811},
     year = 2016,
    month = {may},
    link  = {http://arxiv.org/abs/1605.07811},
    file  = {http://arxiv.org/pdf/1605.07811v1.pdf},
    abstract = {This paper develops a class of meshless methods that are well-suited to statistical inverse problems involving partial differential equations (PDEs). The methods discussed in this paper view the forcing term in the PDE as a random field that induces a probability distribution over the residual error of a symmetric collocation method. This construction enables the solution of challenging inverse problems while accounting, in a rigorous way, for the impact of the discretisation of the forward problem. In particular, this confers robustness to failure of meshless methods, with statistical inferences driven to be more conservative in the presence of significant solver error. In addition, (i) a principled learning-theoretic approach to minimise the impact of solver error is developed, and (ii) the challenging setting of inverse problems with a non-linear forward model is considered. The method is applied to parameter inference problems in which non-negligible solver error must be accounted for in order to draw valid statistical conclusions.}
}

@article{2016arXiv160607686O,
    author = {{Owhadi}, H. and {Zhang}, L.},
    title = "{Gamblets for opening the complexity-bottleneck of implicit schemes for hyperbolic and parabolic ODEs/PDEs with rough coefficients}",
    journal = {ArXiv e-prints},
    issue = {math.NA 1606.07686},
    year = 2016,
    month = jun,
    abstract = {Implicit schemes are popular methods for the integration of time dependent PDEs such as hyperbolic and parabolic PDEs. However the necessity to solve corresponding linear systems at each time step constitutes a complexity bottleneck in their application to PDEs with rough coefficients. We present a generalization of gamblets introduced in arXiv:1503.03467 enabling the resolution of these implicit systems in near-linear complexity and provide rigorous a-priori error bounds on the resulting numerical approximations of hyperbolic and parabolic PDEs. These generalized gamblets induce a multiresolution decomposition of the solution space that is adapted to both the underlying (hyperbolic and parabolic) PDE (and the system of ODEs resulting from space discretization) and to the time-steps of the numerical scheme.},
    link = {http://arxiv.org/abs/1606.07686},
    file = {http://arxiv.org/pdf/1606.07686v1.pdf}
}

@article{owhadi_gamblets_2017,
  title = {Gamblets for opening the complexity-bottleneck of implicit schemes for hyperbolic and parabolic {ODEs}/{PDEs} with rough coefficients},
  volume = {347},
  issn = {00219991},
  url = {http://arxiv.org/abs/1606.07686},
  doi = {10.1016/j.jcp.2017.06.037},
  abstract = {Implicit schemes are popular methods for the integration of time dependent PDEs such as hyperbolic and parabolic PDEs. However the necessity to solve corresponding linear systems at each time step constitutes a complexity bottleneck in their application to PDEs with rough coefficients. We present a generalization of gamblets introduced in {\textbackslash}cite\{OwhadiMultigrid:2015\} enabling the resolution of these implicit systems in near-linear complexity and provide rigorous a-priori error bounds on the resulting numerical approximations of hyperbolic and parabolic PDEs. These generalized gamblets induce a multiresolution decomposition of the solution space that is adapted to both the underlying (hyperbolic and parabolic) PDE (and the system of ODEs resulting from space discretization) and to the time-steps of the numerical scheme.},
  urldate = {2017-09-10},
  journal = {Journal of Computational Physics},
  author = {Owhadi, Houman and Zhang, Lei},
  month = oct,
  year = {2017},
  note = {arXiv: 1606.07686},
  file = {https://arxiv.org/pdf/1606.07686.pdf},
  keywords = {65T60, 65N55, 65N75, 62C99, 42C40, 62M86, Mathematics - Numerical Analysis, Statistics - Machine Learning},
  pages = {99--128}
}

@ARTICLE{2018arXiv180200971D,
   author = {{Dupont}, M. and {En{\ss}lin}, T.},
    title = {Consistency and convergence of simulation schemes in Information field dynamics},
  journal = {ArXiv e-prints},
  archivePrefix = "arXiv",
   eprint = {1802.00971},
  primaryClass = "astro-ph.IM",
  keywords = {Astrophysics - Instrumentation and Methods for Astrophysics},
     year = 2018,
    month = feb,
    abstract = {We explore a new simulation scheme for partial differential equations (PDE's) called Information Field Dynamics (IFD). Information field dynamics attempts to improve on existing simulation schemes by incorporating Bayesian field inference, which seeks to preserve the maximum amount of information about the field being simulated. The field inference is truly Bayesian and thus depends on a notion of prior belief. Here, we analytically prove that a restricted subset of simulation schemes in IFD are consistent, and thus deliver valid predictions in the limit of high resolutions. This has not previously been done for any IFD schemes. This restricted subset is roughly analogous to traditional fixed-grid numerical PDE solvers, given the additional restriction of translational symmetry. Furthermore, given an arbitrary IFD scheme modelling a PDE, it is a-priori not obvious to what order the scheme is accurate in space and time. For this subset of models, we also derive an easy rule-of-thumb for determining the order of accuracy of the simulation. As with all analytic consistency analysis, an analysis for nontrivial systems is intractable, thus these results are intended as a general indicator of the validity of the approach, and it is hoped that the results will generalize.},
    link = {https://arxiv.org/abs/1802.00971},
    file = {https://arxiv.org/pdf/1802.00971}
}

@article{PhysRevE97033314,
  title = {Towards information-optimal simulation of partial differential equations},
  author = {Leike, Reimar H. and En\ss{}lin, Torsten A.},
  journal = {Phys. Rev. E},
  volume = {97},
  issue = {3},
  pages = {033314},
  numpages = {8},
  year = {2018},
  month = {Mar},
  publisher = {American Physical Society},
  doi = {10.1103/PhysRevE.97.033314},
  link = {https://link.aps.org/doi/10.1103/PhysRevE.97.033314},
   abstract = {Most simulation schemes for partial differential equations (PDEs) focus on minimizing a simple error norm of a discretized version of a field. This paper takes a fundamentally different approach; the discretized field is interpreted as data providing information about a real physical field that is unknown. This information is sought to be conserved by the scheme as the field evolves in time. Such an information theoretic approach to simulation was pursued before by information field dynamics (IFD). In this paper we work out the theory of IFD for nonlinear PDEs in a noiseless Gaussian approximation. The result is an action that can be minimized to obtain an information-optimal simulation scheme. It can be brought into a closed form using field operators to calculate the appearing Gaussian integrals. The resulting simulation schemes are tested numerically in two instances for the Burgers equation. Their accuracy surpasses finite-difference schemes on the same resolution. The IFD scheme, however, has to be correctly informed on the subgrid correlation structure. In certain limiting cases we recover well-known simulation schemes like spectral Fourier-Galerkin methods. We discuss implications of the approximations made. }
}

@article{wang2021bayesian,
  title={Bayesian Numerical Methods for Nonlinear Partial Differential Equations},
  author={Wang, Junyang and Cockayne, Jon and Chkrebtii, Oksana and Sullivan, Timothy John and Oates, Chris and others},
  journal={Statistics and Computing},
  year={2021},
  link = {https://arxiv.org/abs/2104.12587}
}

repository: christopheroates/probnum

repo_name: christopheroates/probnum

branch_name: refs/heads/main

gha_language: Python


text:
#container {
  height: 50vh;
  text-align: center;
  display: grid;
}

#image {
  margin: auto;
  height: auto;
  width: 30vh;
}

#show-image-btn {
  margin: auto;
  padding: 0.7em 1.5em;
  font-size: large;
}


text:
require ti-xdais.inc

PV = "6_25_02_11"

SRC_URI[xdaistarball.md5sum] = "33dea671988fa63123f667fd6c0c435d"
SRC_URI[xdaistarball.sha256sum] = "4a71ec361197bbfc49d592afd17b83d21547c6c12a1f5d6fe48f9539f72d951e"

repository: overo/overo-oe-natty

repo_name: overo/overo-oe-natty

branch_name: HEAD

extension: bb


text:
\begin{document} I definitely just have links for things right now. Each
dataset I have is talked about in the Data section
\end{document}


text:
#slider .frame { background-image: none; filter: progid:DXImageTransform.Microsoft.AlphaImageLoader(src='staticfile/images/home/slider-image-bg.png', sizingMethod='image'); }

#slider .buttons span.prev { background-image: none; filter: progid:DXImageTransform.Microsoft.AlphaImageLoader(src='/staticfile/images/home/button-prev.png', sizingMethod='image'); }
#slider .buttons span.next { background-image: none; filter: progid:DXImageTransform.Microsoft.AlphaImageLoader(src='/staticfile/images/home/button-next.png', sizingMethod='image'); }


text:
include(RasPackageImport)

# Import Qhull Cpp target
ras_package_import_target(Qhull::qhullcpp)
ras_package_import_include_dirs(Qhull::qhullcpp Qhull.h PATH_SUFFIXES libqhullcpp)
ras_package_import_library(Qhull::qhullcpp Debug qhullcpp libqhullcpp)
ras_package_import_library(Qhull::qhullcpp Release qhullcpp libqhullcpp)
ras_package_import_define(Qhull TARGETS Qhull::qhullcpp)

# Import Qhull static reentrant target
ras_package_import_target(Qhull::qhullstatic_r)
ras_package_import_include_dirs(Qhull::qhullstatic_r libqhull_r.h PATH_SUFFIXES libqhull_r)
ras_package_import_library(Qhull::qhullstatic_r Debug qhull_r libqhull_r)
ras_package_import_library(Qhull::qhullstatic_r Release qhull_r libqhull_r)
ras_package_import_define(Qhull TARGETS Qhull::qhullstatic_r)

include(FindPackageHandleStandardArgs)
find_package_handle_standard_args(Qhull REQUIRED_VARS
  Qhull_INCLUDE_DIRS)
mark_as_advanced(Qhull_INCLUDE_DIRS)

repository: salespaulo/raycloudtools

repo_name: salespaulo/raycloudtools

extension: cmake