published.bib

@Article {Ahmed:2022,
  author =       {Waqas Ahmed and Sheeba Samuel},
  title =        {{[Re] Nondeterminism and Instability in Neural Network Optimization}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#1}},
  doi =          {10.5281/zenodo.6574623},
  url =          {https://zenodo.org/record/6574623/files/article.pdf},
  code_url =     {https://github.com/wi25hoy/MLRC21_Nondeterminism},
  code_doi =     {},
  code_swh =     {swh:1:dir:75ebcdb9cee4f17c5440b6ca9fd2c6901a929aea},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=BNefkaG73At},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch}
}

@Article {Ankit:2022,
  author =       {Ankit Ankit and Sameer Ambekar and Baradwaj Varadharajan and Mark Alence},
  title =        {{[Re] Counterfactual Generative Networks}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#2}},
  doi =          {10.5281/zenodo.6574625},
  url =          {https://zenodo.org/record/6574625/files/article.pdf},
  code_url =     {https://github.com/ambekarsameer96/FACT_AI/},
  code_doi =     {},
  code_swh =     {swh:1:dir:88d89da0661c0f855f7b6f27c77acac1c2572a93},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=BSHg22G7n0F},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorc deep generative models, counterfactuals}
}

@Article {Ashok:2022,
  author =       {Arjun Ashok and Haswanth Aekula},
  title =        {{[Re] Does Self-Supervision Always Improve Few-Shot Learning?}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#3}},
  doi =          {10.5281/zenodo.6574629},
  url =          {https://zenodo.org/record/6574629/files/article.pdf},
  code_url =     {https://github.com/ashok-arjun/MLRC-2021-Few-Shot-Learning-And-Self-Supervision/},
  code_doi =     {10.5281/zenodo.6508499},
  code_swh =     {swh:1:dir:90d1c4d52eec769a1a18df5bd1f8bd0955f0ac24},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=ScfP3G73CY},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch, few-shot learning, self-supervised learning}
}

@Article {Athanasiadis:2022,
  author =       {Ioannis Athanasiadis and Georgios Moschovis and Alexander Tuoma},
  title =        {{[Re] Weakly-Supervised Semantic Segmentation via Transformer Explainability}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#4}},
  doi =          {10.5281/zenodo.6574631},
  url =          {https://zenodo.org/record/6574631/files/article.pdf},
  code_url =     {https://github.com/athaioan/ViT_Affinity_Reproducibility_Challenge},
  code_doi =     {},
  code_swh =     {swh:1:dir:95342519c89e6957f4f90ee7e51d8724a48d9a56},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=rcEDhGX3AY},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch}
}

@Article {Bagad:2022,
  author =       {Piyush Bagad and Paul Hilders and Jesse Maas and Danilo de Goede},
  title =        {{[Re] Reproducibility Study of “Counterfactual Generative Networks”}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#5}},
  doi =          {10.5281/zenodo.6574635},
  url =          {https://zenodo.org/record/6574635/files/article.pdf},
  code_url =     {https://github.com/danilodegoede/fact-team3/},
  code_doi =     {},
  code_swh =     {swh:1:dir:410075522df668dfae4742564f10b62de0cb8dc6},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=HNlzT3G720t},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, python, pytorch, deep generative models, counterfactuals}
}

@Article {Boer:2022,
  author =       {Sarah de Boer and Radu Alexandru Cosma and Lukas Knobel and Yeskendir Koishekenov and Benjamin Shaffrey},
  title =        {{[Re] Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#6}},
  doi =          {10.5281/zenodo.6574637},
  url =          {https://zenodo.org/record/6574637/files/article.pdf},
  code_url =     {https://github.com/reproducibilityaccount/reproducing-ridesharing},
  code_doi =     {10.5281/zenodo.6501845},
  code_swh =     {swh:1:rev:3beaa469b32b376f92b0fbae34493cdbe0e2ee3c},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=BE3Ms3GXhCF},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, ride-pooling, fairness, LSTM, ILP, resource allocation, matching algorithms, reinforcement learning, machine learning, deep learning, python, pytorch}
}

@Article {Brivio:2022,
  author =       {Matteo Brivio and Çağrı Çöltekin},
  title =        {{[¬Re] Hate Speech Detection based on Sentiment Knowledge Sharing}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#7}},
  doi =          {10.5281/zenodo.6574639},
  url =          {https://zenodo.org/record/6574639/files/article.pdf},
  code_url =     {https://github.com/matteobrv/repro-SKS},
  code_doi =     {10.5281/zenodo.6502870},
  code_swh =     {swh:1:dir:d61b47330cc5c92d7ac4873269faa38a2e3c20bd},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=SSSGs3M7nRY},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, tensorflow, NLP, hate speech, sentiment}
}

@Article {Burger:2022,
  author =       {Maarten Burger and Kaya ter Burg and Sam Titarsolej and Selina Jasmin Khan},
  title =        {{[Re] Reproducibility Study - SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#8}},
  doi =          {10.5281/zenodo.6574641},
  url =          {https://zenodo.org/record/6574641/files/article.pdf},
  code_url =     {https://github.com/kayatb/reproduce_SCOUTER},
  code_doi =     {},
  code_swh =     {swh:1:dir:a294d795e2f9e00a93e9955b70c86a28b1c310d0},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=HZNlq3fmhRF},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, SCOUTER, XAI, Explainable, AI, Interpretable, Reproducibility, Attention, Self-attention, Computer Vision, python, pytorch}
}

@Article {Buvanesh:2022,
  author =       {Anirudh Buvanesh and Madhur Panwar},
  title =        {{[Re] AdaBelief Optimizer: Adapting Stepsizes by the Belief in Observed Gradients}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#9}},
  doi =          {10.5281/zenodo.6574643},
  url =          {https://zenodo.org/record/6574643/files/article.pdf},
  code_url =     {https://github.com/anirudhb11/Adabelief-Optimizer-RC},
  code_doi =     {},
  code_swh =     {swh:1:dir:53eeebe14e9d02d912fc3c58c375b5095e8db941},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=B9gDnMmn0t},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, optimizers, image classification, language modelling, generative adversarial networks}
}

@Article {Dasu:2022,
  author =       {Vishnu Asutosh Dasu and Midhush Manohar T.K.},
  title =        {{[Re] GANSpace: Discovering Interpretable GAN Controls}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#10}},
  doi =          {10.5281/zenodo.6574645},
  url =          {https://zenodo.org/record/6574645/files/article.pdf},
  code_url =     {https://github.com/midsterx/ReGANSpace},
  code_doi =     {10.5281/zenodo.6511501},
  code_swh =     {swh:1:dir:4dc4de7856350a4671d97840c5f9ae013c275112},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=BtZVD2f7n0F},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, tensorflow, numpy, gans, image synthesis}
}

@Article {Drabent:2022,
  author =       {Karolina Drabent and Stefan Wijnja and Thijs Sluijter and Konrad Bereda},
  title =        {{[Re] Replication study of "Privacy-preserving Collaborative Learning"}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#11}},
  doi =          {10.5281/zenodo.6574647},
  url =          {https://zenodo.org/record/6574647/files/article.pdf},
  code_url =     {https://github.com/stfwn/ats-privacy-replication},
  code_doi =     {10.5281/zenodo.6508136},
  code_swh =     {swh:1:dir:1b0c9cb880eedcbdfb56c51afc8ed74ba437e14b},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=SY84JTG73CK},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch, pytorch lightning, federated learning, data augmentation, privacy}
}

@Article {Dzubur:2022,
  author =       {Benjamin Džubur},
  title =        {{[Re] A Cluster-based Approach for Improving Isotropy in Contextual Embedding Space}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#12}},
  doi =          {10.5281/zenodo.6574649},
  url =          {https://zenodo.org/record/6574649/files/article.pdf},
  code_url =     {https://github.com/Benidzu/isotropy_reproduction},
  code_doi =     {},
  code_swh =     {swh:1:dir:407d517fb5299301bcfc7f8aa461a4c3bf7c36b0},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=rxWeB3zQ2CY},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, natural language processing, python}
}

@Article {Eaton:2022,
  author =       {Erica Eaton and Pirouz Naghavi},
  title =        {{[Re] Reproduction and Extension of "Queens are Powerful too: Mitigating Gender Bias in Dialogue Generation"}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#13}},
  doi =          {10.5281/zenodo.6574651},
  url =          {https://zenodo.org/record/6574651/files/article.pdf},
  code_url =     {https://github.com/Pnaghavi/Mitigating-Gender-Bias-in-Generated-Text},
  code_doi =     {},
  code_swh =     {swh:1:dir:320f7080ccd0edd611da07e9dbd9dbe4bbd18758},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=StblE2MQ3AY},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, natural language processing, deep learning, python, bias mitigation}
}

@Article {Sinha:2022,
  author =       {Koustuv Sinha and Jesse Dodge and Sasha Luccioni and Jessica Zosa Forde and Sharath Chandra Raparthy and Joelle Pineau and Robert Stojnic},
  title =        {{ML Reproducibility Challenge 2021}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  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 {Eijkelboom:2022,
  author =       {Floor Eijkelboom and Mark Fokkema and Anna Lau and Luuk Verheijen},
  title =        {{[Re] Reproduction Study of Variational Fair Clustering}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#14}},
  doi =          {10.5281/zenodo.6574653},
  url =          {https://zenodo.org/record/6574653/files/article.pdf},
  code_url =     {https://github.com/MarkiemarkF/FACT},
  code_doi =     {10.5281/zenodo.6508390},
  code_swh =     {swh:1:dir:016245babcdc02c28ac98547de32f7270c79f81f},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=rq8fRhMm20F},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, python, pytorch, clustering, fairness}
}

@Article {Geijn:2022,
  author =       {Chase van de Geijn and Victor Kyriacou and Irene Papadopoulou and Vasiliki Vasileiou},
  title =        {{[Re] Explaining in Style: Training a GAN to explain a classifier in StyleSpace}},
  journal =      {None},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#15}},
  doi =          {10.5281/zenodo.6574655},
  url =          {https://zenodo.org/record/6574655/files/article.pdf},
  code_url =     {https://github.com/irenepap2/Re_StylEx.git},
  code_doi =     {10.5281/zenodo.6508290},
  code_swh =     {swh:1:dir:f0871f3a14e536717d3225180942c4a385ce39e3},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=SK8gAhfX2AK},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch}
}

@Article {Hardy:2022,
  author =       {Ian Hardy},
  title =        {{[Re] An Implementation of Fair Robust Learning}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#16}},
  doi =          {10.5281/zenodo.6574657},
  url =          {https://zenodo.org/record/6574657/files/article.pdf},
  code_url =     {https://github.com/Ian-Hardy/Fair_Robust_Modeling},
  code_doi =     {10.5281/zenodo.6506696},
  code_swh =     {swh:1:dir:bd6142ce2ce3fd99fab9918a6c6754115035abe4},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=Sczshz7h0K},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch, adversarial training, fairness, robustness}
}

@Article {Hoppe:2022,
  author =       {Tobias Höppe and Agnieszka Miszkurka and Dennis Bogatov Wilkman},
  title =        {{[Re] Understanding Self-Supervised Learning Dynamics without Contrastive Pairs}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#17}},
  doi =          {10.5281/zenodo.6574659},
  url =          {https://zenodo.org/record/6574659/files/article.pdf},
  code_url =     {https://github.com/miszkur/SelfSupervisedLearning},
  code_doi =     {10.5281/zenodo.6508184},
  code_swh =     {swh:1:dir:ec5169f4713c6c67088d980c76f1c25bc1c399bc},
  data_url =     {https://www.cs.toronto.edu/~kriz/cifar.html},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=r4xe3nMQ3AY},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch}
}

@Article {Jiles:2022,
  author =       {Richard Jiles and Mohna Chakraborty},
  title =        {{[Re] Domain Generalization using Causal Matching}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#18}},
  doi =          {10.5281/zenodo.6574661},
  url =          {https://zenodo.org/record/6574661/files/article.pdf},
  code_url =     {https://github.com/rjiles/causalmatching},
  code_doi =     {10.5281/zenodo.6529518},
  code_swh =     {swh:1:dir:08875ab42adddf57b8019c82f4e5889d1009743c},
  data_url =     {https://github.com/rjiles/causalmatching},
  data_doi =     {10.5281/zenodo.6529518},
  review_url =   {https://openreview.net/forum?id=r43elaGmhCY},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch}
}

@Article {Kirca:2022,
  author =       {Isa-Ali Kirca and Daniël Hamerslag and Afra Baas and Juno Prent},
  title =        {{[¬Re] Reproducibility Study of 'Exacerbating Algorithmic Bias through Fairness Attacks' }},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#19}},
  doi =          {10.5281/zenodo.6574663},
  url =          {https://zenodo.org/record/6574663/files/article.pdf},
  code_url =     {https://github.com/DCHamerslag/FACT},
  code_doi =     {10.5281/zenodo.6491095},
  code_swh =     {swh:1:dir:25564a437957494e991b5205e262159e75d84d59;},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=rKbgh3fXnRK},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python}
}

@Article {Kolkman:2022,
  author =       {Guilly Kolkman and Jan Athmer and Alex Labro and Maksymilian Kulicki},
  title =        {{[Re] Strategic classification made practical: reproduction}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#20}},
  doi =          {10.5281/zenodo.6574665},
  url =          {https://zenodo.org/record/6574665/files/article.pdf},
  code_url =     {https://github.com/GuillyK/FACT-ai},
  code_doi =     {},
  code_swh =     {swh:1:dir:31ff8f4d7da6e70c88e4d28ba0c18ee5f04ac424;},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=rNgg03fXnRY},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch}
}

@Article {Bosch:2022,
  author =       {Evaline Bosch and Rutger Ettes and Daan Korporaal and Gijs van Meer},
  title =        {{[Re] Replication study of 'Explaining in Style: Training a GAN to explain a classifier in StyleSpace'}},
  journal =      {None},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#21}},
  doi =          {10.5281/zenodo.6574667},
  url =          {https://zenodo.org/record/6574667/files/article.pdf},
  code_url =     {https://github.com/Gijsvanmeer/FACTinAI},
  code_doi =     {10.5281/zenodo.6508302},
  code_swh =     {swh:1:dir:1d0dbddb7bc7060aee89621b45cea15325dca1b1},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=BtIz0nz7hRY},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch, AI, GANs, SyleSpace, reconstruction}
}

@Article {Tafuro:2022,
  author =       {Matteo Tafuro and Andrea Lombardo and Tin Hadži Veljković and Lasse Becker-Czarnetzki},
  title =        {{[Re] Exacerbating Algorithmic Bias through Fairness Attacks}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#22}},
  doi =          {10.5281/zenodo.6574669},
  url =          {https://zenodo.org/record/6574669/files/article.pdf},
  code_url =     {https://github.com/imandrealombardo/FACT-AI},
  code_doi =     {},
  code_swh =     {swh:1:dir:b775237e47e9de16827cb9cae83423d090faa4f8},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=H4lzChGmhCK},
  type =         {Replication},
  language =     {python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, rescience x, reproducibility, machine learning, deep learning, fairness, python, tensorflow, adversarial attack, fairness attack, algorithmic bias, influence attack on fairness, anchoring attack}
}

@Article {De~Luisa:2022,
  author =       {Andra\v{z} De~Luisa},
  title =        {{[Re] Thompson Sampling for Bandits with Clustered Arms}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#23}},
  doi =          {10.5281/zenodo.6574671},
  url =          {https://zenodo.org/record/6574671/files/article.pdf},
  code_url =     {https://github.com/andrazdeluisa/reproducibility_challenge},
  code_doi =     {10.5281/zenodo.6498328},
  code_swh =     {swh:1:dir:d1d7fa93e952cf14154d5415f253b6507af22833},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=r5LS3fmh0t},
  type =         {Replication},
  language =     {R},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {Multi-armed bandits, Thompson sampling, R, rescience c, machine learning}
}

@Article {Mast:2022,
  author =       {Diego van der Mast and Soufiane Ben Haddou and Jacky Chu and Jaap Stefels},
  title =        {{[Re] Replication Study of "Fairness and Bias in Online Selection"}},
  journal =      {None},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#24}},
  doi =          {10.5281/zenodo.6574673},
  url =          {https://zenodo.org/record/6574673/files/article.pdf},
  code_url =     {https://github.com/Di-ayy-go/fact-ai},
  code_doi =     {10.5281/zenodo.6518051},
  code_swh =     {swh:1:dir:45176f5005ed390a349cd01e61ed37711095879e},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=SNeep2MXn0K},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, rescience x, Python, machine learning, fairness}
}

@Article {Chen:2022,
  author =       {Andy Chen and Shion Matsumoto and Rohan Sinha Varma},
  title =        {{[Re] Projection-based Algorithm for Updating the TruncatedSVD of Evolving Matrices}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#25}},
  doi =          {10.5281/zenodo.6574675},
  url =          {https://zenodo.org/record/6574675/files/article.pdf},
  code_url =     {https://github.com/andyzfchen/truncatedSVD},
  code_doi =     {},
  code_swh =     {swh:1:dir:4116fecf6ec4ac207cdad025ec62b25839a75678},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=HN2xWpMQ30K},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, python, pytorch}
}

@Article {Mehta:2022,
  author =       {Aryan Mehta and Karan Uppal and Kaushal Jadhav and Monish Natarajan and Mradul Agrawal and Debashish Chakravarty},
  title =        {{[Re] Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic Segmentation}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#26}},
  doi =          {10.5281/zenodo.6574677},
  url =          {https://zenodo.org/record/6574677/files/article.pdf},
  code_url =     {https://github.com/karan-uppal3/BANA},
  code_doi =     {},
  code_swh =     {swh:1:dir:24495d2fbb5d4af66607261c2171ed42173a72cf},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=rUQllTGQhAY},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch}
}

@Article {Mikler:2022,
  author =       {Szymon Mikler},
  title =        {{[Re] Reproducibility Study: Comparing Rewinding and Fine-tuning in Neural Network Pruning}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#27}},
  doi =          {10.5281/zenodo.6574679},
  url =          {https://zenodo.org/record/6574679/files/article.pdf},
  code_url =     {https://github.com/gahaalt/reproducing-comparing-rewinding-and-finetuning},
  code_doi =     {10.5281/zenodo.6519109},
  code_swh =     {swh:1:dir:886a4c9a0bdecdbf65f2cab3ae7404a6796bc451},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=HxWEL2zQ3AK},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, tensorflow, computer vision, pruning}
}

@Article {Nalmpantis:2022,
  author =       {Angelos Nalmpantis and Apostolos Panagiotopoulos and John Gkountouras and Konstantinos Papakostas},
  title =        {{[Re] Exacerbating Algorithmic Bias through Fairness Attacks}},
  journal =      {None},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#28}},
  doi =          {10.5281/zenodo.6574681},
  url =          {https://zenodo.org/record/6574681/files/article.pdf},
  code_url =     {https://github.com/toliz/fairness-attacks},
  code_doi =     {10.5281/zenodo.6505214},
  code_swh =     {swh:1:dir:224b71f5d3c02f260427e2f7c492b6db98c65638},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=rYLMJ6zX3RF},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, python, pytorch, fairness, adversarial attacks}
}

@Article {Neplenbroek:2022,
  author =       {Vera Neplenbroek and Sabijn Perdijk and Victor Prins},
  title =        {{[Re] Replication study of 'Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling'}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#29}},
  doi =          {10.5281/zenodo.6574683},
  url =          {https://zenodo.org/record/6574683/files/article.pdf},
  code_url =     {https://github.com/Veranep/rideshare-replication},
  code_doi =     {10.5281/zenodo.6501799},
  code_swh =     {swh:1:dir:f5439c1a7a15c4eb709da6f32eb252679a1d44bd},
  data_url =     {https://www1.nyc.gov/site/tlc/about/tlc-trip-record-data.page},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=BEhgn2zm3CK},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch, ridesharing, fairness}
}

@Article {Galatolo:2022,
  author =       {Alessio Galatolo and Alfred Nilsson},
  title =        {{[Re] Replicating and Improving GAN2Shape Through Novel Shape Priors and Training Steps}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#30}},
  doi =          {10.5281/zenodo.6574685},
  url =          {https://zenodo.org/record/6574685/files/article.pdf},
  code_url =     {https://github.com/alessioGalatolo/GAN-2D-to-3D},
  code_doi =     {},
  code_swh =     {swh:1:dir:531d1456baa3bb553ce549785158be7005c682c7},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=B8mxkTzX2RY},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch, gan2shape, 3d}
}

@Article {Panigrahi:2022,
  author =       {Siba Smarak Panigrahi and Sohan Patnaik},
  title =        {{[Re] Value Alignment Verification}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#31}},
  doi =          {10.5281/zenodo.6574687},
  url =          {https://zenodo.org/record/6574687/files/article.pdf},
  code_url =     {https://github.com/AIExL/vav_rc2021},
  code_doi =     {},
  code_swh =     {swh:1:dir:4d43ea96458cc573dd2b57208fae0b12f8da896f},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=BFLM3nMmhCt},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, value alignment verification, reinforcement learning, machine learning, python}
}

@Article {Petcu:2022,
  author =       {Roxana Petcu and Pim Praat and Jeroen Wijnen and Manolis Rerres},
  title =        {{[Re] Replication Study of "Fairness and Bias in Online Selection"}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#32}},
  doi =          {10.5281/zenodo.6574689},
  url =          {https://zenodo.org/record/6574689/files/article.pdf},
  code_url =     {https://github.com/pimpraat/FACT-Ai},
  code_doi =     {},
  code_swh =     {swh:1:dir:da9cb18759db5ecf30608639d8b35a4b247a483d},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=S9gs3MmhAY},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, online selection, prophet problem, secretary problem, fairness, bias, Python}
}

@Article {Peters:2022,
  author =       {Nils Peters and Joy Crosbie and Rachel van\'t Hull and Marius Strampel},
  title =        {{[¬Re] Reproducing 'Fair Selective Classification via Sufficiency'}},
  journal =      {None},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#33}},
  doi =          {10.5281/zenodo.6574691},
  url =          {https://zenodo.org/record/6574691/files/article.pdf},
  code_url =     {https://github.com/MLRC2022FSCS/FSCS},
  code_doi =     {10.5281/zenodo.6479342},
  code_swh =     {swh:1:dir:effcbb5800e91db9053cb59c68bbc097a10da7cf},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=r9Leh2M7hCt},
  type =         {Replication},
  language =     {Python 3},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, classification, selective classification, sufficiency, machine learning, Python 3}
}

@Article {Ranjan:2022,
  author =       {Rohit Ranjan and Himadri Bhakta and Animesh Jha and Parv Maheshwari},
  title =        {{[Re] Differentiable Spatial Planning using Transformers}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#34}},
  doi =          {10.5281/zenodo.6574693},
  url =          {https://zenodo.org/record/6574693/files/article.pdf},
  code_url =     {https://github.com/sirmisscriesalot/Differentiable-Spatial-Planning-using-Transformers},
  code_doi =     {10.5281/zenodo.6475614},
  code_swh =     {swh:1:dir:6aa6080e642126b1166661d245a4f594a777889b},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=HFUI1pfQnCF},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch}
}

@Article {Rucks:2022,
  author =       {Nick Rucks and Tobias Uelwer and Stefan Harmeling},
  title =        {{[Re] Solving Phase Retrieval With a Learned Reference}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#35}},
  doi =          {10.5281/zenodo.6574695},
  url =          {https://zenodo.org/record/6574695/files/article.pdf},
  code_url =     {https://github.com/tuelwer/machine-learning-reproducibility-challenge-2021},
  code_doi =     {},
  code_swh =     {swh:1:dir:0a7ba3d1b8f4d4e2ee09a62ddfbe2e8a124d6b1e},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=rlWzUnM72RF},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, phase retrieval, machine learning, python, pytorch}
}

@Article {Sen:2022,
  author =       {Roopsa Sen and Sidharth Sinha and Animesh Jha and Parv Maheshwari},
  title =        {{[Re] Reproducibility Report: Contrastive Learning of Socially-aware Motion Representations}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#36}},
  doi =          {10.5281/zenodo.6574697},
  url =          {https://zenodo.org/record/6574697/files/article.pdf},
  code_url =     {https://github.com/RoopsaSen/social-nce-trajectron-plus-plus},
  code_doi =     {10.5281/zenodo.6511007},
  code_swh =     {swh:1:dir:ba72ac2acf3bac942d9b3a66e51091e6bcce6617},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=SIQEl6f7h0Y},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch}
}

@Article {Shukla:2022,
  author =       {Abhishek Shukla and Sourya Roy and Yogesh Chawla and Avi Amalanshu and Shubhendu Pandey and Rudransh Agrawal and Aditya Uppal and Viswesh N and Pradipto Mondal and Anubhab Dasgupta and Debashis Chakravarty},
  title =        {{[Re] From goals, waypoints and paths to longterm human trajectory forecasting}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#37}},
  doi =          {10.5281/zenodo.6574699},
  url =          {https://zenodo.org/record/6574699/files/article.pdf},
  code_url =     {https://github.com/Viswesh-N/MLRC-2021},
  code_doi =     {},
  code_swh =     {swh:1:dir:3ddeeb8325dbac3f85d05e49621a9adef5f44ebb},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=HV2zgpM7n0F},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, trajectory prediction, machine learning, deep learning, python, pytorch}
}

@Article {Stropnik:2022,
  author =       {Vid Stropnik and Maruša Oražem},
  title =        {{[Re] Graph Edit Networks}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#38}},
  doi =          {10.5281/zenodo.6574701},
  url =          {https://zenodo.org/record/6574701/files/article.pdf},
  code_url =     {https://github.com/MarusaOrazem/reproducibility_challenge},
  code_doi =     {10.5281/zenodo.6505384},
  code_swh =     {swh:1:dir:a48bde44f1ef0b6f060687ea7b8b164a97b0931e},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=H5lOnzXhAY},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {machine learning, network analysis, graph machine learning, pytorch, python, rescience c}
}

@Article {Kljun:2022,
  author =       {Maša Kljun and Matija Teršek and Domen Vreš},
  title =        {{[Re] Learning to count everything}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#39}},
  doi =          {10.5281/zenodo.6574703},
  url =          {https://zenodo.org/record/6574703/files/article.pdf},
  code_url =     {https://github.com/tersekmatija/re-LearningToCountEverything},
  code_doi =     {10.5281/zenodo.6508260},
  code_swh =     {swh:1:dir:cf19f5a717c777cd1097e938ef4e6bdb735f71c7},
  data_url =     {https://drive.google.com/file/d/1ymDYrGs9DSRicfZbSCDiOu0ikGDh5k6S/view?usp=sharing},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=HKbgd3zmh0t},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {few-shot learning, few-shot counting, CNN, counting data set, rescience c, machine learning, python}
}

@Article {Togt:2022,
  author =       {Jille van der Togt and Lea Tiyavorabun and Matteo Rosati and Giulio Starace},
  title =        {{[Re] Badder Seeds: Reproducing the Evaluation of Lexical Methods for Bias Measurement}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#40}},
  doi =          {10.5281/zenodo.6574705},
  url =          {https://zenodo.org/record/6574705/files/article.pdf},
  code_url =     {https://github.com/thesofakillers/badder-seeds},
  code_doi =     {10.5281/zenodo.6480966},
  code_swh =     {swh:1:dir:13ff45fd249e765a221d49f701c32d45b64ee675},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=HcIxA3Mm2CF},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch, nlp, bias, seeds}
}

@Article {Trojer:2022,
  author =       {Žiga Trojer},
  title =        {{[Re] Transparent Object Tracking Benchmark}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#41}},
  doi =          {10.5281/zenodo.6574707},
  url =          {https://zenodo.org/record/6574707/files/article.pdf},
  code_url =     {https://github.com/trojerz/TOTB-reproducability},
  code_doi =     {10.5281/zenodo.6475970},
  code_swh =     {swh:1:dir:b80fa866c01389a46dde8b6f419d893d127f1025},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=HxZZV3MQ20Y},
  type =         {Replication},
  language =     {Python, Matlab},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, tracking, computer vision, python, pytorch, matlab}
}

@Article {Vleuten:2022,
  author =       {Noah van der Vleuten and Tadija Radusinović and Rick Akkerman and Meilina Reksoprodjo},
  title =        {{[Re] Explaining in Style: Training a GAN to explain a classifier in StyleSpace}},
  journal =      {None},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#42}},
  doi =          {10.5281/zenodo.6574709},
  url =          {https://zenodo.org/record/6574709/files/article.pdf},
  code_url =     {https://github.com/NoahVl/Explaining-In-Style-Reproducibility-Study},
  code_doi =     {10.5281/zenodo.6512392},
  code_swh =     {swh:1:dir:04e11a55f476b115b40fd6af9d06ed70eb248535},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=SYUxyazQh0Y},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch, explainable ai, xai, gan, stylegan2, stylex}
}

@Article {Shulev:2022,
  author =       {Velizar Shulev and Paul Verhagen and Shuai Wang and Jennifer Zhuge},
  title =        {{[Re] Replication Study of DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#43}},
  doi =          {10.5281/zenodo.6574711},
  url =          {https://zenodo.org/record/6574711/files/article.pdf},
  code_url =     {https://github.com/ShuaiWang97/UvA_FACT2022},
  code_doi =     {10.5281/zenodo.6515893},
  code_swh =     {swh:1:dir:78ac8ec89fd95397fd635e8d9e885e1d5ac6c039},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=SVx46hzmhRK},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch, reproducibility, causal graphs, debiasing}
}

@Article {Warmerdam:2022,
  author =       {Alfonso Taboada Warmerdam and Lodewijk Loerakker and Lucas Meijer and Ole Nissen},
  title =        {{[Re] Privacy-preserving collaborative learning with automatic transformation search}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#44}},
  doi =          {10.5281/zenodo.6574713},
  url =          {https://zenodo.org/record/6574713/files/article.pdf},
  code_url =     {https://github.com/Linkerbrain/fact-ai-2021-project},
  code_doi =     {10.5281/zenodo.6482966},
  code_swh =     {swh:1:dir:30aff8e620b5a2f17c4ec653b4b6fe80272fdaff},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=S9Iepnz7hRY},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {rescience c, machine learning, deep learning, python, pytorch}
}

@Article {Wilschut:2022,
  author =       {Romana Isabelle Wilschut and Thomas Paul Alexandre Wiggers and Roman Sebastiaan Oort and Thomas Arthur van Orden},
  title =        {{[Re] Robust Counterfactual Explanations on Graph Neural Networks}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#45}},
  doi =          {10.5281/zenodo.6574715},
  url =          {https://zenodo.org/record/6574715/files/article.pdf},
  code_url =     {https://github.com/RomanOort/FACTAI},
  code_doi =     {},
  code_swh =     {swh:1:dir:5744faf1da0fd9b520c8aa72a0608b78f0a91e7a},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=HWNgihGX20Y},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {counterfactual, explanations, GNN, robust, graph neural networks, interpretation, explainable AI, decision logic, reproducibility, python, rescience c, machine learning}
}

@Article {Ylmaz:2022,
  author =       {Doğa Yılmaz and Furkan Kınlı and Barış Özcan and Furkan Kıraç},
  title =        {{[Re] Lifting 2D StyleGAN for 3D-Aware Face Generation}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#46}},
  doi =          {10.5281/zenodo.6574719},
  url =          {https://zenodo.org/record/6574719/files/article.pdf},
  code_url =     {https://github.com/yilmazdoga/lifting-2d-stylegan-for-3d-aware-face-generation},
  code_doi =     {},
  code_swh =     {swh:1:dir:c4289f0be8edafa7d050efc178bd1bc9bed0bbdc},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=BcNonfQ3RY},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {face generation, generative networks, machine learning, rescience c}
}

@Article {Zrimsek:2022,
  author =       {Urša Zrimšek},
  title =        {{[Re] Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction}},
  journal =      {ReScience C},
  year =         {2022},
  month =        {5},
  volume =       {8},
  number =       {2},
  pages =        {{#47}},
  doi =          {10.5281/zenodo.6574721},
  url =          {https://zenodo.org/record/6574721/files/article.pdf},
  code_url =     {https://github.com/zrimseku/Reproducibility-Challenge},
  code_doi =     {10.5281/zenodo.6511807},
  code_swh =     {swh:1:dir:6eedc394f714587f35840bee0aac3e675bfa6c5a},
  data_url =     {},
  data_doi =     {},
  review_url =   {https://openreview.net/forum?id=Hc8GOhfmhRF},
  type =         {Replication},
  language =     {Python},
  domain =       {ML Reproducibility Challenge 2021},
  keywords =     {multi-type inter-novel-protein interaction, graph neural networks, fair evaluation, python, rescience c, replication, machine learning}
}