all_articles.bib

@Article {Sinha:2021,
  author =       {Koustuv Sinha and Jesse Dodge and Sasha Luccioni and Jessica Zosa Forde and Robert Stojnic and Joelle Pineau},
  title =        {{ML Reproducibility Challenge 2020}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  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 {Albanis:2021,
  author =       {Georgios Albanis and Nikolaos Zioulis and Anargyros Chatzitofis and Anastasios Dimou and Dimitrios Zarpalas and Petros Daras},
  title =        {{[Re] On end-to-end 6{DoF} object pose estimation and robustness to object scale}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#2}},
  doi =          {10.5281/zenodo.4833219},
  url =          {https://zenodo.org/record/4833219/files/article.pdf},
  code_url =     {https://github.com/tzole1155/EndToEndObjectPose},
  code_doi =     {},
  code_swh =     {swh:1:dir:5e754c06b0dac970857b31733766fb9a268edee6},
  data_url =     {https://vcl3d.github.io/UAVA/},
  data_doi =     {10.5281/zenodo.3994337},
  review_url =   {https://openreview.net/forum?id=PCpGvUrwfQB},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {rescience c, rescience x , python, pytorch, object pose estimation}
}

@Article {Arvind:2021,
  author =       {Mayur Arvind and Mustansir Mama},
  title =        {{[Re] Neural Networks Fail to Learn Periodic Functions and How to Fix It}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#3}},
  doi =          {10.5281/zenodo.4833389},
  url =          {https://zenodo.org/record/4833389/files/article.pdf},
  code_url =     {https://github.com/mayurak47/Reproducibility_Challenge},
  code_doi =     {10.5281/zenodo.4696245},
  code_swh =     {swh:1:dir:8887a5d45dac9427457c6b5869728e1ba3cfd37c},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=ysFCiXtCOj},
  type =         {Replication},
  language =     {python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {periodic functions, activation, python}
}

@Article {Teule:2021,
  author =       {Tobias Teule and Nienke Reints and Chris Al Gerges and Pauline Baanders},
  title =        {{[Re] Deep Fair Clustering for Visual Learning}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#4}},
  doi =          {10.5281/zenodo.4833547},
  url =          {https://zenodo.org/record/4833547/files/article.pdf},
  code_url =     {https://github.com/topteulen/UVA-FACT},
  code_doi =     {},
  code_swh =     {swh:1:dir:7058002f161d29f18e52a18ebe326b7911b1b616;},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=DXVAJGohUKs},
  type =         {Replication},
  language =     {python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {rescience c, rescience x,python, Deep clustering}
}

@Article {Garg:2021,
  author =       {Prateek Garg and Lakshya Singhal and Ashish Sardana},
  title =        {{[Re] Training Binary Neural Networks using the Bayesian Learning Rule}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#5}},
  doi =          {10.5281/zenodo.4833681},
  url =          {https://zenodo.org/record/4833681/files/article.pdf},
  code_url =     {https://github.com/prateekstark/training-binary-neural-network},
  code_doi =     {10.5281/zenodo.4716863},
  code_swh =     {swh:1:dir:904c01b8e4ac0d4acd1f5fe667511d5a9234d8da},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=bhiGno-Cxq},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {rescience c, machine learning, deep learning, binary neural network, python, pytorch}
}

@Article {Habacker:2021,
  author =       {Rahel Habacker and Andrew Harrison and Mathias Parisot and Ard Snijders},
  title =        {{[Re] Reproducing Learning to Deceive With Attention-Based Explanations}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#6}},
  doi =          {10.5281/zenodo.4834146},
  url =          {https://zenodo.org/record/4834146/files/article.pdf},
  code_url =     {https://github.com/MatPrst/deceptive-attention-reproduced},
  code_doi =     {10.5281/zenodo.4692668},
  code_swh =     {},
  data_url =     {https://github.com/MatPrst/deceptive-attention-reproduced/tree/main/deceptive-attention/src/classification/data},
  data_doi =     {10.5281/zenodo.4686793},
  review_url =   {https://openreview.net/forum?id=-rn9m0Gt6AQ},
  type =         {Replication},
  language =     {Python 3},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {rescience c, rescience x, Python}
}

@Article {Holdijk:2021,
  author =       {Lars Holdijk and Maarten Boon and Stijn Henckens and Lysander de Jong},
  title =        {{[Re] Parameterized Explainer for Graph Neural Network}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#7}},
  doi =          {10.5281/zenodo.4834242},
  url =          {https://zenodo.org/record/4834242/files/article.pdf},
  code_url =     {https://github.com/LarsHoldijk/RE-ParameterizedExplainerForGraphNeuralNetworks},
  code_doi =     {},
  code_swh =     {swh:1:dir:541677177d4dbb9dc5b612dfc41373fad40b08f0},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=8JHrucviUf},
  type =         {Replication},
  language =     {English},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {rescience c, rescience x}
}

@Article {Kim:2021,
  author =       {Sunnie S. Y. Kim and Sharon Zhang and Nicole Meister and Olga Russakovsky},
  title =        {{[Re] Don't Judge an Object by Its Context: Learning to Overcome Contextual Bias}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#8}},
  doi =          {10.5281/zenodo.4834352},
  url =          {https://zenodo.org/record/4834352/files/article.pdf},
  code_url =     {https://github.com/princetonvisualai/ContextualBias},
  code_doi =     {},
  code_swh =     {swh:1:dir:bc41dd1d3cbd9c97754c3da0ee20ba2273b742fd},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=PRXM8-O9PKd},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {rescience c, rescience x}
}

@Article {Li:2021,
  author =       {Ci Li and Ruibo Tu and Hui Zhang},
  title =        {{[Re] Reimplementation of FixMatch and Investigation on Noisy (Pseudo) Labels and Confirmation Errors of FixMatch}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#9}},
  doi =          {10.5281/zenodo.4834442},
  url =          {https://zenodo.org/record/4834442/files/article.pdf},
  code_url =     {https://github.com/Celiali/FixMatch.git},
  code_doi =     {},
  code_swh =     {swh:1:dir:6c3389cac6218bdd28599fea638c6c5def256081},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=3VXeifKSaTE},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {rescience c, rescience x}
}

@Article {Liiv:2021,
  author =       {Toomas Liiv and Einar Lennelöv and Aron Norén},
  title =        {{[Re] A Reproduction of Ensemble Distribution Distillation}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#10}},
  doi =          {10.5281/zenodo.4834516},
  url =          {https://zenodo.org/record/4834516/files/article.pdf},
  code_url =     {https://github.com/lennelov/endd-reproduce},
  code_doi =     {},
  code_swh =     {swh:1:dir:2c366708175b2ed7c83ce6b33a80dd43c8aad915},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=p1BXNUcTFsN},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {rescience c, rescience x, uncertainty estimation, ensemble distribution distillation, tensorflow}
}

@Article {Stephen:2021,
  author =       {Kevin Stephen and Varun Menon},
  title =        {{[Re] Learning Memory Guided Normality for Anomaly Detection}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#11}},
  doi =          {10.5281/zenodo.4834610},
  url =          {https://zenodo.org/record/4834610/files/article.pdf},
  code_url =     {https:/github.com/alchemi5t/MNADrc},
  code_doi =     {10.5281/zenodo.4681515},
  code_swh =     {1:dir:120b52bc3dfe115b3329698a39ea71c7cd5862d1},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=vvLWTXkJ2Zv},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {rescience c, rescience x}
}

@Article {Mentes:2021,
  author =       {Sami Menteş and Furkan Kınlı and Barış Özcan and Furkan Kıraç},
  title =        {{[Re] Spatial-Adaptive Network for Single Image Denoising}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#12}},
  doi =          {10.5281/zenodo.4834672},
  url =          {https://zenodo.org/record/4834672/files/article.pdf},
  code_url =     {https://github.com/sami-automatic/SADNet_Replication},
  code_doi =     {},
  code_swh =     {swh:1:dir:1c60d43a0fe927c1f1287adefd252804c2f273b9},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=yiAI9QN9nYt&noteId=SMFjCY6qG8},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {image denoising, image restoration, image processing}
}

@Article {Mizrahi:2021,
  author =       {David Mizrahi and Oğuz Kaan Yüksel and Aiday Marlen Kyzy},
  title =        {{[Re] Can gradient clipping mitigate label noise?}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#13}},
  doi =          {10.5281/zenodo.4834744},
  url =          {https://zenodo.org/record/4834744/files/article.pdf},
  code_url =     {https://github.com/dmizr/phuber},
  code_doi =     {},
  code_swh =     {swh:1:dir:3363073199859b8bec0c4362e47aa1e786985793},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=TM_SgwWJA23},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {rescience c, machine learning, deep learning, label noise, python, pytorch}
}

@Article {Kireev:2021,
  author =       {Klim Kireev and Amirkeivan Mohtashami and Ehsan Pajouheshgar},
  title =        {{[Re] Warm-Starting Neural Network Training}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#14}},
  doi =          {10.5281/zenodo.4834856},
  url =          {https://zenodo.org/record/4834856/files/article.pdf},
  code_url =     {https://github.com/CS-433/cs-433-project-2-fesenjoon},
  code_doi =     {},
  code_swh =     {swh:1:dir:a7205bcd48196c1391d8c56414a1e20c39b52aa7},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=N43DVxrjCw},
  type =         {Replication},
  language =     {python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {warm-starting, generalization, deep learning}
}

@Article {P:2021,
  author =       {Jishnu Jaykumar P and Ashish Sardana},
  title =        {{[Re] Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#15}},
  doi =          {10.5281/zenodo.4834942},
  url =          {https://zenodo.org/record/4834942/files/article.pdf},
  code_url =     {https://github.com/jishnujayakumar/MLRC2020-EmbedKGQA},
  code_doi =     {},
  code_swh =     {swh:1:dir:c95bc4fec7023c258c7190975279b5baf6ef6725},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=VFAwCMdWY7},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {knowledge graph, embeddings, multi-hop, question-answering, deep learning}
}

@Article {Reijnaers:2021,
  author =       {Damiaan J. W. Reijnaers and Daniël B. van de Pavert and Giguru Scheuer and Liang Huang},
  title =        {{[Re] Explaining Groups of Points in Low-Dimensional Representations}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#16}},
  doi =          {10.5281/zenodo.4835056},
  url =          {https://zenodo.org/record/4835056/files/article.pdf},
  code_url =     {https://github.com/damiaanr/fact-ai},
  code_doi =     {10.5281/zenodo.4686025},
  code_swh =     {swh:1:dir:df71f3541f882bfb2474dc177b8eaba31f905d9d},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=hq3TxQK5cox},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {rescience c, rescience x, python, counterfactual explanations, transitive global translations, dimensionality reduction, explainable artificial intelligence}
}

@Article {Deprez:2021,
  author =       {Hidde Lekanne gezegd Deprez and Geerten Rijsdijk and Bart de Rooij and Wouter Zwerink},
  title =        {{[Re] Reproducing 'Identifying through flows for recovering latent representations'}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#17}},
  doi =          {10.5281/zenodo.4839595},
  url =          {https://zenodo.org/record/4839595/files/article.pdf},
  code_url =     {https://github.com/HiddeLekanne/Reproducibility-Challenge-iFlow},
  code_doi =     {10.5281/zenodo.4704869},
  code_swh =     {swh:1:dir:a08aac73d57611c3d2abc0a55437d7bae40d02f7},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=8jmIpypMzE},
  type =         {Replication},
  language =     {Python 3},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {identifiability, iFlow, iVAE, Normalizing Flows, Python 3},
  note = "new version with corrected page/article number. original DOI was 10.5281/zenodo.4835150"
}

@Article {Balsells Rodas:2021,
  author =       {Balsells Rodas, Carles and Canal Anton, Oleguer and Taschin, Federico},
  title =        {{[Re] Hamiltonian Generative Networks}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#18}},
  doi =          {10.5281/zenodo.4835278},
  url =          {https://zenodo.org/record/4835278/files/article.pdf},
  code_url =     {https://github.com/CampusAI/Hamiltonian-Generative-Networks},
  code_doi =     {10.5281/zenodo.4673473},
  code_swh =     {swh:1:dir:7c7cee4b1c4dc7dfa46b4b4bf5c3b8b20deb5b26},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=Zszk4rXgesL},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {Hamiltonian, generative network, variational, python, pytorch}
}

@Article {Schneider:2021,
  author =       {Maja Schneider and Marco Körner},
  title =        {{[Re] Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#19}},
  doi =          {10.5281/zenodo.4835356},
  url =          {https://zenodo.org/record/4835356/files/article.pdf},
  code_url =     {https://github.com/maja601/pytorch-psetae},
  code_doi =     {},
  code_swh =     {swh:1:dir:631305811058b775406ae624095e3ec66ace6437},
  data_url =     {http://www.eurocrops.tum.de/},
  data_doi =     {},
  review_url =   {},
  type =         {Replication},
  language =     {python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {rescience c, rescience x, python, transformer, self-attention, time series, crop classification, earth observation}
}

@Article {Sheverdin:2021,
  author =       {Arsen Sheverdin and Alko Knijff and Noud Corten and Georg Lange},
  title =        {{[Re] Reproducibility report of "Interpretable Complex-Valued Neural Networks for Privacy Protection"}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#20}},
  doi =          {10.5281/zenodo.4835431},
  url =          {https://zenodo.org/record/4835431/files/article.pdf},
  code_url =     {https://github.com/GANA-FACT-AI/gana-fact-ai},
  code_doi =     {},
  code_swh =     {swh:1:dir:16f75580c3619b9e0b00b6dceef8e5bf2f5a47c4},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=P30M7d9DyXw},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {rescience c, rescience x, machine, learning, deep, complex, valued, neural, network, python, pytorch}
}

@Article {Sundar:2021,
  author =       {Varun Sundar and Rajat Vadiraj Dwaraknath},
  title =        {{[Re] Rigging the Lottery: Making All Tickets Winners}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#21}},
  doi =          {10.5281/zenodo.4835564},
  url =          {https://zenodo.org/record/4835564/files/article.pdf},
  code_url =     {https://github.com/varun19299/rigl-reproducibility},
  code_doi =     {},
  code_swh =     {swh:1:dir:0707870fafa16ef60dc64071e1aed482e373e75f},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=riCIeP6LzEE},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {rescience c, rescience x, python, pytorch, sparse-networks}
}

@Article {Bouwman:2021,
  author =       {Pieter Bouwman and Yun Li and Rogier van der Weerd and Frank Verhoef},
  title =        {{[Re] Reproducibility study - Does enforcing diversity in hidden states of LSTM-Attention models improve transparency?}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#22}},
  doi =          {10.5281/zenodo.4835592},
  url =          {https://zenodo.org/record/4835592/files/article.pdf},
  code_url =     {https://github.com/MotherOfUnicorns/FACT_AI_project},
  code_doi =     {},
  code_swh =     {swh:1:dir:19a8073757cc142f8f50eb44014aca87cad0b8bf},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=lE0wqKGROKa},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {Attention, NLP, Transparency, Explainability, Faithfulness, Plausibility, Reproducibility, LSTM, ReScience}
}

@Article {Verhoeven:2021,
  author =       {Ivo Verhoeven and Xinyi Chen and Qingzhi Hu and Mario Holubar},
  title =        {{[Re] Replication Study of 'Generative causal explanations of black-box classifiers'}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#23}},
  doi =          {10.5281/zenodo.4835600},
  url =          {https://zenodo.org/record/4835600/files/article.pdf},
  code_url =     {https://github.com/shin-ee-chen/UvA_FACT_2021},
  code_doi =     {},
  code_swh =     {swh:1:dir:9d960937f2b11bb67b53bbe4eaa940c14cadf9d1},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=Vqtf4kZg2j},
  type =         {Replication},
  language =     {python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {rescience c, rescience x, python, causal explanations, variational  autoencoders,  explainable  artificial  intelligence, post-hoc explanation}
}

@Article {Verma:2021,
  author =       {Rajeev Verma and Jim J. O. Wagemans and Paras Dahal and Auke Elfrink},
  title =        {{[Re] Explaining Groups of Points in Low-Dimensional Representations}},
  journal =      {ReScience C},
  year =         {2021},
  month =        {5},
  volume =       {7},
  number =       {2},
  pages =        {{#24}},
  doi =          {10.5281/zenodo.4835602},
  url =          {https://zenodo.org/record/4835602/files/article.pdf},
  code_url =     {https://github.com/elfrink1/FACT},
  code_doi =     {},
  code_swh =     {swh:1:dir:445130f59283e6dce7df5eb72dd346a5c57c9230},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=cqAHExg2f},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2020},
  keywords =     {rescience c, rescience x}
}