René's URL Explorer Experiment


Title: csinva (Chandan Singh) · GitHub

Open Graph Title: csinva - Overview

X Title: csinva - Overview

Description: Senior researcher @Microsoft interpreting ML models in science and medicine. PhD from UC Berkeley. - csinva

Open Graph Description: Senior researcher @Microsoft interpreting ML models in science and medicine. PhD from UC Berkeley. - csinva

X Description: Senior researcher @Microsoft interpreting ML models in science and medicine. PhD from UC Berkeley. - csinva

Opengraph URL: https://github.com/csinva

X: @github

direct link

Domain: patch-diff.githubusercontent.com

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request-idB81A:2ACEE1:1F67DC:2ACD88:696FD95A
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og:image:altSenior researcher @Microsoft interpreting ML models in science and medicine. PhD from UC Berkeley. - csinva
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csinvahttps://patch-diff.githubusercontent.com/csinva/csinva
Homepagehttps://csinva.io/
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Google Scholarhttps://scholar.google.com/citations?hl=en&user=vPYz4QwAAAAJ
LinkedInhttps://www.linkedin.com/in/csinva/
https://patch-diff.githubusercontent.com/csinva#-interpretable-models--dataset-explanations
https://github.com/csinva/imodels
https://camo.githubusercontent.com/444f9c6587a9d5b45b756b98c75b0bdda9a7bff067cebbf7d0879468975af193/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6373696e76612f696d6f64656c733f636f6c6f723d253233454545267374796c653d666c61742d737175617265266c6162656c3d254532254144253930266c6162656c436f6c6f723d253233454545
JOSS 2021https://joss.theoj.org/papers/10.21105/joss.03192
PNAS 2022https://arxiv.org/abs/2201.11931
ICML 2022https://arxiv.org/abs/2202.00858
https://github.com/csinva/imodelsX
https://camo.githubusercontent.com/0513ace58416b2d9cbb0d78e60e0f39175c023b20a6dec1fe5874ef7ee762e7e/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6373696e76612f696d6f64656c73583f636f6c6f723d253233454545267374796c653d666c61742d737175617265266c6162656c3d254532254144253930266c6162656c436f6c6f723d253233454545
Nature Communications 2023https://arxiv.org/abs/2209.11799
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EMNLP 2023https://arxiv.org/abs/2310.14034
https://camo.githubusercontent.com/46cc61541e66086b1e1864393ff742c057dfff6196855250aee21bfabb1b4f9c/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6373696e76612f747265652d70726f6d70743f636f6c6f723d253233454545267374796c653d666c61742d737175617265266c6162656c3d254532254144253930266c6162656c436f6c6f723d253233454545
ICLR workshop 2023https://arxiv.org/abs/2210.01848
https://camo.githubusercontent.com/35f08c358dabcb8744bc4f6e8b7d67e630ba0c0875e7f55e440fa86641a88cb6/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6373696e76612f696e7465727072657461626c652d6175746f70726f6d7074696e673f636f6c6f723d253233454545267374796c653d666c61742d737175617265266c6162656c3d254532254144253930266c6162656c436f6c6f723d253233454545
NeurIPS workshop 2023https://arxiv.org/abs/2305.09863
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NeurIPS 2024https://arxiv.org/abs/2405.16714
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adaptive-waveletshttps://github.com/Yu-Group/adaptive-wavelet-distillation
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NeurIPS 2021https://arxiv.org/abs/2107.09145
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https://github.com/csinva/csinva.github.io
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JOSS 2021https://joss.theoj.org/papers/10.21105/joss.03895
https://patch-diff.githubusercontent.com/csinva#-interpreting-neural-networks
deep-explanation-penalizationhttps://github.com/laura-rieger/deep-explanation-penalization
https://camo.githubusercontent.com/6665232a13ec2128d58d77722346d9016ebe6008c5c415de9bd34440cd723285/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6c617572612d7269656765722f646565702d6578706c616e6174696f6e2d70656e616c697a6174696f6e3f636f6c6f723d253233454545267374796c653d666c61742d737175617265266c6162656c3d254532254144253930266c6162656c436f6c6f723d253233454545
ICML 2020https://arxiv.org/abs/1909.13584
hierarchical-dnn-interpretationshttps://github.com/csinva/hierarchical-dnn-interpretations
https://camo.githubusercontent.com/b80e9799a2e599eb404831a4dfc7af729754ad9eee0ac8d17ba9057c6c367b37/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6373696e76612f68696572617263686963616c2d646e6e2d696e746572707265746174696f6e733f636f6c6f723d253233454545267374796c653d666c61742d737175617265266c6162656c3d254532254144253930266c6162656c436f6c6f723d253233454545
ICLR 2019https://arxiv.org/abs/1806.05337
transformation-importancehttps://github.com/csinva/transformation-importance
https://camo.githubusercontent.com/f7cb7ecf7196545ecf30fa5d4bdee9da94b78193b4d0d96b539c2ccf38fac810/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6373696e76612f7472616e73666f726d6174696f6e2d696d706f7274616e63653f636f6c6f723d253233454545267374796c653d666c61742d737175617265266c6162656c3d254532254144253930266c6162656c436f6c6f723d253233454545
ICLR Workshop 2020https://arxiv.org/abs/2003.01926
https://patch-diff.githubusercontent.com/csinva#-data-science-problems
automated-brain-explanationshttps://github.com/microsoft/automated-brain-explanations
https://camo.githubusercontent.com/c198a637b48a122608e09bff7d4b03f931cbda89a1f956b8ab3b4105effd8633/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f6d6963726f736f66742f6175746f6d617465642d627261696e2d6578706c616e6174696f6e733f636f6c6f723d253233454545267374796c653d666c61742d737175617265266c6162656c3d254532254144253930266c6162656c436f6c6f723d253233454545
arxiv 2024https://arxiv.org/abs/2410.00812
clinical-rule-developmenthttps://github.com/csinva/clinical-rule-development
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PLOS DH, 2022https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000076
Nature SR, 2025https://www.nature.com/articles/s41598-025-89996-w
medRxiv, 2025https://www.medrxiv.org/content/10.1101/2025.02.12.25320965v1
clinical-rule-vettinghttps://github.com/Yu-Group/rule-stress-testing
https://camo.githubusercontent.com/92622e2c04ff784eed82c90b9a40f41f2ab588b9b88f38308b19b34ce1af3080/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f59752d47726f75702f72756c652d7374726573732d74657374696e673f636f6c6f723d253233454545267374796c653d666c61742d737175617265266c6162656c3d254532254144253930266c6162656c436f6c6f723d253233454545
clinical-self-verificationhttps://github.com/microsoft/clinical-self-verification
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HACHIhttps://github.com/jjfenglab/HACHI
BC-LLMhttps://github.com/jjfeng/bc-llm
covid19-severity-predictionhttps://github.com/Yu-Group/covid19-severity-prediction
https://camo.githubusercontent.com/bbcb612dc6d11421164f2e4d0b5a73ddcbf16cc7e1c629eaf00151b6ece95103/68747470733a2f2f696d672e736869656c64732e696f2f6769746875622f73746172732f59752d47726f75702f636f76696431392d73657665726974792d70726564696374696f6e3f636f6c6f723d253233454545267374796c653d666c61742d737175617265266c6162656c3d254532254144253930266c6162656c436f6c6f723d253233454545
HDSR 2021https://hdsr.mitpress.mit.edu/pub/p6isyf0g/release/4
molecular-partner-predictionhttps://github.com/Yu-Group/molecular-partner-prediction
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https://patch-diff.githubusercontent.com/csinva#various-aspects-of-deep-learning-and-machine-learning
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arxiv 2019https://arxiv.org/abs/1905.07631
matching-with-ganshttps://github.com/csinva/matching-with-gans
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CVPR workshop 2021https://arxiv.org/abs/2103.13455
data-viz-utilshttps://github.com/csinva/data-viz-utils
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JMLR 2021https://arxiv.org/abs/2006.10189
https://patch-diff.githubusercontent.com/csinva#projects-advised
pastahttps://github.com/QingruZhang/PASTA
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ICLR 2024https://arxiv.org/abs/2311.02262
Qingru Zhanghttps://github.com/QingruZhang
meta-treehttps://github.com/EvanZhuang/MetaTree
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TMLR 2024https://arxiv.org/abs/2402.03774
Yufan Zhuanghttps://github.com/EvanZhuang
sim-dinohttps://github.com/RobinWu218/SimDINO
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ICML 2025https://arxiv.org/abs/2502.10385
Ziyang Wuhttps://github.com/RobinWu218
explanation-consistency-finetuninghttps://github.com/yandachen/explanation-consistency-finetuning
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COLING 2025https://arxiv.org/abs/2401.13986
Yanda Chenhttps://github.com/yandachen
induction-gramhttps://github.com/ejkim47/induction-gram
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arXiv 2024https://arxiv.org/abs/2401.13986
Eunji Kimhttps://github.com/ejkim47
Sriya Mantenahttps://github.com/SriyaM
https://patch-diff.githubusercontent.com/csinva#open-source-contributions
autogluonhttps://github.com/awslabs/autogluon
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big-benchhttps://github.com/google/BIG-bench
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iterative-random-foresthttps://github.com/Yu-Group/iterative-Random-Forest
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interpretable-ml-bookhttps://github.com/christophM/interpretable-ml-book
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https://patch-diff.githubusercontent.com/csinva#mini-projects
hummingbird-trackinghttps://github.com/csinva/hummingbird-tracking
imodels-experimentshttps://github.com/Yu-Group/imodels-experiments
cookiecutter-ml-researchhttps://github.com/csinva/cookiecutter-ml-research
nano-descriptionshttps://github.com/csinva/nano-descriptions
news-title-biashttps://github.com/csinva/news-title-bias
java-mini-gameshttps://github.com/csinva/mini-games
imodels-datahttps://github.com/csinva/imodels-data
news-balancerhttps://github.com/csinva/news-balancer
arxiv-copierhttps://github.com/csinva/arxiv-copier
dnn-experimentshttps://github.com/csinva/dnn-experiments
max-activation-interpretation-pytorchhttps://github.com/csinva/max-activation-interpretation-pytorch
acronym-generatorhttps://github.com/csinva/acronym-generator
hpa-interphttps://github.com/csinva/hpa-interp
sensible-local-interpretationshttps://github.com/csinva/sensible-local-interpretations
global-sports-analysishttps://github.com/csinva/global-sports-analysis
mouse-brain-decodinghttps://github.com/csinva/mouse-brain-decoding
imodelshttps://patch-diff.githubusercontent.com/csinva/imodels
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