GithubHelp home page GithubHelp logo

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

🌳 Interpretable models / dataset explanations

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

Interpretability for text. Contains Aug-imodels (Nature Communications 2023) , Tree-Prompt (EMNLP 2023) , iPrompt (ICLR workshop 2023) , SASC (NeurIPS workshop 2023) , and QA-Embs (arXiv)

adaptive-wavelets Adaptive, interpretable wavelets (NeurIPS 2021)

🤖 General-purpose AI packages and cheatsheets

Notes and resources on AI

Utilities for trustworthy data-science (JOSS 2021)

🧠 Interpreting neural networks

deep-explanation-penalization Penalizing neural-network explanations (ICML 2020)

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

transformation-importance Feature importance for transformations (ICLR Workshop 2020)

📊 Data-science problems

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

clinical-rule-vetting General pipeline for deriving clinical decision rules

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

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

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

disentangled-attribution-curves Attribution curves for interpreting tree ensembles trees (arxiv 2019)

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

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

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

Projects advised

pasta Post-hoc Attention Steering for LLMs (ICLR 2024), led by Qingru Zhang

meta-tree Learning a Decision Tree Algorithm with Transformers (arXiv 2024), led by Yufan Zhuang

explanation-consistency-finetuning Consistent Natural-Language Explanations (arXiv 2024), led by Yanda Chen

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 , awesome-llm-interpretability , executable-books , deep-fMRI-dataset

Mini-projects

hummingbird-tracking, imodels-experiments, cookiecutter-ml-research, 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, ...

Chandan Singh's Projects

acronym-generator icon acronym-generator

Generator acronyms given a sequence of words (useful for making paper titles).

arxiv-copier icon arxiv-copier

Extension for copying the title + url of an arXiv page via right click

csinva.github.io icon csinva.github.io

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

data-viz-utils icon data-viz-utils

Functions for easily making publication-quality figures with matplotlib.

dnn-experiments icon dnn-experiments

A set of scripts and experiments making it easier to analyze deep learning empirically.

fmri icon fmri

Experiments with language fMRI data from Alex Huth lab

imodels icon imodels

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

imodels-data icon imodels-data

Preprocessed data for various popular tabular datasets to go along with imodels.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.