@article{Rougier:2018,
  doi = {10.1038/d41586-018-04628-w},
  year = {2018},
  month = apr,
  publisher = {Springer Nature},
  volume = {556},
  number = {7701},
  pages = {309--309},
  author = {Rougier, Nicolas P. and Hinsen, Konrad},
  title = {Code reviewing puts extra demands on referees },
  journal = {Nature},
}

@article{Science:2018,
  doi = {10.1126/science.359.6377.725},
  author = {Hutson, Matthew},
  url = {http://science.sciencemag.org/content/359/6377/725},
  year = {2018},
  month = feb,
  volume = {359},
  number = {6377},
  title = {Artificial intelligence faces a replication crisis},
  journal = {Science},
}

@Misc{Roboto:2011,
  author =       {Christian Robertson},
  title =        {The Roboto family of fonts (Google)},
  url =          {https://github.com/google/roboto},
  year =         2011,
  note =         {Apache License, verison 2.0},
}

@Misc{SourceSerifPro:2014,
  author =       {Frank Grießhammer},
  title =        {Source Serif Pro (Adobe Systems)},
  url =          {https://github.com/adobe-fonts/source-serif-pro},
  year =         2014,
  note =         {SIL Open Font License, version 1.1},
}

@Misc{SourceCodePro:2012,
  author =       {Paul D. Hunt},
  title =        {Source Code Pro (Adobe Systems)},
  url =          {https://github.com/adobe-fonts/source-code-pro},
  year =         2012,
  note =         {SIL Open Font License, version 1.1},
}

@article{Topalidou:2015,
  author =       {Topalidou, Meropi and Rougier, Nicolas P.},
  title =        {{[Re] Interaction between cognitive and motor cortico-basal
                  ganglia loops during decision making: a computational study}},
  journal =      {ReScience},
  year =         2015,
  volume =       1,
  number =       1,
  doi =          {10.5281/zenodo.27944},
}

@article{Rougier:2017,
  doi =          {10.7717/peerj-cs.142},
  author =       {Nicolas P. Rougier and Konrad Hinsen and Frédéric Alexandre
                  and Thomas Arildsen and Lorena Barba and Fabien
                  C. Y. Benureau and C. Titus Brown and Pierre de Buyl and Ozan
                  Caglayan and Andrew P. Davison and Marc André Delsuc and
                  Georgios Detorakis and Alexandra K. Diem and Damien Drix and
                  Pierre Enel and Benoît Girard and Olivia Guest and Matt
                  G. Hall and Rafael Neto Henriques and Xavier Hinaut and Kamil
                  S Jaron and Mehdi Khamassi and Almar Klein and Tiina Manninen
                  and Pietro Marchesi and Dan McGlinn and Christoph Metzner and
                  Owen L. Petchey and Hans Ekkehard Plesser and Timothée Poisot
                  and Karthik Ram and Yoav Ram and Etienne Roesch and Cyrille
                  Rossant and Vahid Rostami and Aaron Shifman and Joseph
                  Stachelek and Marcel Stimberg and Frank Stollmeier and
                  Federico Vaggi and Guillaume Viejo and Julien Vitay and Anya
                  Vostinar and Roman Yurchak and Tiziano Zito},
  title =        {{Sustainable computational science: the ReScience
                  initiative}},
  journal =      {{PeerJ} Computer Science},
  month =        12,
  volume =       3,
  pages =        {e142},
  year =         2017,
  github =       {https://github.com/ReScience/ReScience-article-2},
  keywords =     {journal},
  tags =         {OS},
}

@article{Sinha:2022,
  author = {Sinha, Koustuv and Dodge, Jesse and Luccioni, Sasha and Forde, Jessica Zosa and Raparthy, Sharath Chandra and Pineau, Joelle and Stojnic, Robert},
  title = {{ML Reproducibility Challenge 2021}},
  journal = {ReScience C},
  year = {2022},
  month = may,
  volume = {8},
  number = {2},
  pages = {{48}},
  doi = {10.5281/zenodo.6574723},
  url = {https://zenodo.org/record/6574723/files/article.pdf},
  code_url = {},
  code_doi = {},
  code_swh = {},
  data_url = {},
  data_doi = {},
  review_url = {},
  type = {Editorial},
  language = {Python},
  domain = {ML Reproducibility Challenge 2021},
  keywords = {rescience c, machine learning, deep learning, python, pytorch}
}

@article{Sinha:2021,
  author = {Sinha, Koustuv and Dodge, Jesse and Luccioni, Sasha and Forde, Jessica Zosa and Stojnic, Robert and Pineau, Joelle},
  title = {{ML Reproducibility Challenge 2020}},
  journal = {ReScience C},
  year = {2021},
  month = may,
  volume = {7},
  number = {2},
  pages = {{1}},
  doi = {10.5281/zenodo.4833117},
  url = {https://zenodo.org/record/4833117/files/article.pdf},
  code_url = {},
  code_doi = {},
  code_swh = {},
  data_url = {},
  data_doi = {},
  review_url = {},
  type = {Editorial},
  language = {},
  domain = {},
  keywords = {machine learning, neurips, reproducibility challenge}
}

@article{Sinha:2020,
  author = {Sinha, Koustuv and Pineau, Joelle and Forde, Jessica and Ke, Rosemary Nan and Larochelle, Hugo},
  title = {{NeurIPS 2019 Reproducibility Challenge}},
  journal = {ReScience C},
  year = {2020},
  month = may,
  volume = {6},
  number = {2},
  pages = {{11}},
  doi = {10.5281/zenodo.3818627},
  url = {https://zenodo.org/record/3818627/files/article.pdf},
  code_url = {},
  code_doi = {},
  code_swh = {},
  data_url = {},
  data_doi = {},
  review_url = {},
  type = {Editorial},
  language = {},
  domain = {},
  keywords = {machine learning, neurips, reproducibility challenge}
}

@article{Pineau:2019,
  author = {Pineau, Joelle and Sinha, Koustuv and Fried, Genevieve and Ke, Rosemary Nan and Larochelle, Hugo},
  title = {{ICLR Reproducibility Challenge 2019}},
  journal = {ReScience C},
  year = {2019},
  month = may,
  volume = {5},
  number = {2},
  pages = {{5}},
  doi = {10.5281/zenodo.3158244},
  url = {https://zenodo.org/record/3158244/files/article.pdf},
  code_url = {},
  code_doi = {},
  data_url = {},
  data_doi = {},
  review_url = {https://github.com/ReScience/submissions/issues/5},
  type = {Editorial},
  language = {},
  domain = {},
  keywords = {machine learning, ICLR, reproducibility challenge}
}

@inproceedings{kolek2022cartoon,
  title={Cartoon explanations of image classifiers},
  author={Kolek, Stefan and Nguyen, Duc Anh and Levie, Ron and Bruna, Joan and Kutyniok, Gitta},
  booktitle={Computer Vision--ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23--27, 2022, Proceedings, Part XII},
  pages={443--458},
  year={2022},
  organization={Springer}
}

@inproceedings{deng2009imagenet,
  title={Imagenet: A large-scale hierarchical image database},
  author={Deng, Jia and Dong, Wei and Socher, Richard and Li, Li-Jia and Li, Kai and Fei-Fei, Li},
  booktitle={2009 IEEE conference on computer vision and pattern recognition},
  pages={248--255},
  year={2009},
  organization={Ieee}
}

@article{CIFAR10,
title= {CIFAR-10 (Canadian Institute for Advanced Research)},
journal= {},
author= {Alex Krizhevsky and Vinod Nair and Geoffrey Hinton},
year= {},
url= {http://www.cs.toronto.edu/~kriz/cifar.html},
abstract= {The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images. 

The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the remaining images in random order, but some training batches may contain more images from one class than another. Between them, the training batches contain exactly 5000 images from each class. },
keywords= {Dataset},
terms= {}
}

@article{simonyan2014very,
  title={Very deep convolutional networks for large-scale image recognition},
  author={Simonyan, Karen and Zisserman, Andrew},
  journal={arXiv preprint arXiv:1409.1556},
  year={2014}
}

@inproceedings{howard2019searching,
  title={Searching for mobilenetv3},
  author={Howard, Andrew and Sandler, Mark and Chu, Grace and Chen, Liang-Chieh and Chen, Bo and Tan, Mingxing and Wang, Weijun and Zhu, Yukun and Pang, Ruoming and Vasudevan, Vijay and others},
  booktitle={Proceedings of the IEEE/CVF international conference on computer vision},
  pages={1314--1324},
  year={2019}
}

@inproceedings{he2016deep,
  title={Deep residual learning for image recognition},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={770--778},
  year={2016}
}

@article{dosovitskiy2020image,
  title={An image is worth 16x16 words: Transformers for image recognition at scale},
  author={Dosovitskiy, Alexey and Beyer, Lucas and Kolesnikov, Alexander and Weissenborn, Dirk and Zhai, Xiaohua and Unterthiner, Thomas and Dehghani, Mostafa and Minderer, Matthias and Heigold, Georg and Gelly, Sylvain and others},
  journal={arXiv preprint arXiv:2010.11929},
  year={2020}
}

@article{heiss2020distribution,
  title={In-distribution interpretability for challenging modalities},
  author={Hei{\ss}, Cosmas and Levie, Ron and Resnick, Cinjon and Kutyniok, Gitta and Bruna, Joan},
  journal={arXiv preprint arXiv:2007.00758},
  year={2020}
}

% pixelRDE
@article{macdonald2019rate,
  title={A rate-distortion framework for explaining neural network decisions},
  author={MacDonald, Jan and W{\"a}ldchen, Stephan and Hauch, Sascha and Kutyniok, Gitta},
  journal={arXiv preprint arXiv:1905.11092},
  year={2019}
}

% Grad CAM
@inproceedings{selvaraju2017grad,
  title={Grad-cam: Visual explanations from deep networks via gradient-based localization},
  author={Selvaraju, Ramprasaath R and Cogswell, Michael and Das, Abhishek and Vedantam, Ramakrishna and Parikh, Devi and Batra, Dhruv},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  pages={618--626},
  year={2017}
}

% Integrated Gradients
@inproceedings{sundararajan2017axiomatic,
  title={Axiomatic attribution for deep networks},
  author={Sundararajan, Mukund and Taly, Ankur and Yan, Qiqi},
  booktitle={International conference on machine learning},
  pages={3319--3328},
  year={2017},
  organization={PMLR}
}

% Smooth Grad
@article{smilkov2017smoothgrad,
  title={Smoothgrad: removing noise by adding noise},
  author={Smilkov, Daniel and Thorat, Nikhil and Kim, Been and Vi{\'e}gas, Fernanda and Wattenberg, Martin},
  journal={arXiv preprint arXiv:1706.03825},
  year={2017}
}

% Guided Backprop
@article{springenberg2014striving,
  title={Striving for simplicity: The all convolutional net},
  author={Springenberg, Jost Tobias and Dosovitskiy, Alexey and Brox, Thomas and Riedmiller, Martin},
  journal={arXiv preprint arXiv:1412.6806},
  year={2014}
}

% LRP
@article{LRP,
author = {Lapuschkin, Sebastian and Binder, Alexander and Montavon, Grégoire and Klauschen, Frederick and Müller, Klaus-Robert and Samek, Wojciech},
year = {2015},
month = {07},
pages = {e0130140},
title = {On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation},
volume = {10},
journal = {PLoS ONE},
doi = {10.1371/journal.pone.0130140}
}

% LIME
@inproceedings{ribeiro2016should,
  title={" Why should i trust you?" Explaining the predictions of any classifier},
  author={Ribeiro, Marco Tulio and Singh, Sameer and Guestrin, Carlos},
  booktitle={Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining},
  pages={1135--1144},
  year={2016}
}

@inproceedings{redmon2016you,
  title={You only look once: Unified, real-time object detection},
  author={Redmon, Joseph and Divvala, Santosh and Girshick, Ross and Farhadi, Ali},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={779--788},
  year={2016}
}