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@conda-forge @BerkeleyML @Yu-Group @lumosvision @response4life
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csinva/README.md 

Hi there 👋 I'm Chandan, a Senior Researcher at Microsoft Research working on interpretable machine learning.
Homepage / Twitter / LinkedIn / Google Scholar

🤖 General-purpose AI packages and cheatsheets

Slides, paper notes, class notes, blog posts, and research on ML, stat, and AI

Making it easier to build stable, trustworthy data-science pipelines (JOSS 2021)

🌳 Interpretable models / dataset explanations

Interpretable and accurate predictive modeling, sklearn-compatible (JOSS 2021) -- contains FIGS (arXiv 2022) and HSTree (ICML 2022)

Library to explain a dataset in natural language -- contains Emb-GAM (arXiv 2022) and iPrompt (arXiv 2022)

adaptive-wavelets Adaptive, interpretable wavelets across domains (NeurIPS 2021)

🧠 Interpreting neural networks

hierarchical-dnn-interpretations Hierarchical interpretations for neural network predictions (ICLR 2019)

deep-explanation-penalization Interpretations are useful: penalizing explanations to align neural networks with prior knowledge (ICML 2020)

transformation-importance Transformation Importance with Applications to Cosmology (ICLR Workshop 2020)

📊 Data-science problems

covid19-severity-prediction Extensive and accessible COVID-19 data + forecasting for counties and hospitals (HDSR 2021)

iai-clinical-decision-rule Interpretable clinical decision rules for predicting intra-abdominal injury (PLOS Digital Health 2022)

rule-vetting General pipeline for deriving clinical decision rules

molecular-partner-prediction Predicting successful CME events using only clathrin markers

Various aspects of deep learning and machine learning

gan-vae-pretrained-pytorch Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch

gpt2-paper-title-generator Generating paper titles with GPT-2

disentangled-attribution-curves Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees (arxiv 2019)

matching-with-gans Matching in GAN latent space for better bias benchmarking. (CVPR workshop 2021)

mdl-complexity Revisiting complexity and the bias-variance tradeoff (TOPML workshop 2021)

data-viz-utils Functions for easily making publication-quality figures with matplotlib

Open-source contributions

Major: autogluon , big-bench , nl-augmenter

Minor: conference-acceptance-rates , iterative-random-forest , interpretable-ml-book , awesome-interpretable-machine-learning , awesome-machine-learning-interpretability , executable-books

Mini-projects

hummingbird-tracking, imodels-experiments, nano-descriptions, news-title-bias, java-mini-games, imodels-data, news-balancer, arxiv-copier, dnn-experiments, max-activation-interpretation-pytorch, acronym-generator, hpa-interp, sensible-local-interpretations, global-sports-analysis, mouse-brain-decoding, ...

Pinned

  1. csinva.github.io Public

    Slides, paper notes, class notes, blog posts, and research on ML 📉, statistics 📊, and AI 🤖.

    HTML 441 99

  2. imodels Public

    Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

    Jupyter Notebook 975 96

  3. hierarchical-dnn-interpretations Public

    Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)

    Jupyter Notebook 110 21

  4. laura-rieger/deep-explanation-penalization Public

    Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584

    Jupyter Notebook 113 15

  5. Yu-Group/covid19-severity-prediction Public

    Extensive and accessible COVID-19 data + forecasting for counties and hospitals. 📈

    Jupyter Notebook 213 88

  6. gan-vae-pretrained-pytorch Public

    Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.

    Jupyter Notebook 143 40

1,033 contributions in the last year

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Contribution activity

December 2022

Created 35 commits in 7 repositories

Created an issue in paperswithcode/galai that received 1 comment

Preprocessing script for moleculenet / uniprot?

Hello, I'd like to investigate / replicate the Galactica results on scientific domains. Is it possible to release the script used to preprocess the…

1 comment