csinva

clinical-rule-development

Building and vetting clinical decision rules.

csinva.github.io

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

gan-vae-pretrained-pytorch

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

gpt-paper-title-generator

Generating paper titles (and more!) with GPT trained on data scraped from arXiv.

hierarchical-dnn-interpretations

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

imodels

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

imodelsX

Interpret text data using LLMs (scikit-learn compatible).

interpretable-embeddings

Interpretable text embeddings by asking LLMs yes/no questions (NeurIPS 2024)

iprompt

Finding semantically meaningful and accurate prompts.

automated-brain-explanations

Generating and validating natural-language explanations for the brain.

csinva/imodels

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

csinva/csinva.github.io

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

csinva/gan-vae-pretrained-pytorch

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

csinva/imodelsX

Interpret text data using LLMs (scikit-learn compatible).

csinva/gpt-paper-title-generator

Generating paper titles (and more!) with GPT trained on data scraped from arXiv.

csinva/iprompt

Finding semantically meaningful and accurate prompts.

csinva/interpretable-embeddings

Interpretable text embeddings by asking LLMs yes/no questions (NeurIPS 2024)

csinva/tree-prompt

Tree prompting: easy-to-use scikit-learn interface for improved prompting.

csinva/matching-with-gans

Matching in GAN latent space for better bias benchmarking and semantic image editing. 👶🏻🧒🏾👩🏼‍🦰👱🏽‍♂️👴🏾

csinva/data-viz-utils

Functions for easily making publication-quality figures with matplotlib.

csinva/mdl-complexity

MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".

csinva/cookiecutter-ml-research

A logical, reasonably standardized, but flexible project structure for conducting ml research 🍪

csinva/clinical-rule-development

Building and vetting clinical decision rules.

csinva/clinical-rule-survey

Analyzing clinical decision instruments through the lens of data and large language models.

csinva/tree-prompt-experiments

Create a tree of prompts during training that improves efficiency and accuracy.

csinva/imodels-data

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

csinva/pybaobab-fork

Fork of pybaobabdt adding more customization.

csinva/fmri

Experiments with language fMRI data from Alex Huth lab

csinva/tpr-fmri

csinva/analyzing-patient-perspectives

Analyzing interview data from the PediDOSE EFIC interviews using LLMs.

csinva/news-title-bias

Scraping and analyzing political bias in news titles using data from allsides.com

csinva/Conference-Acceptance-Rate

Acceptance rates for the major AI conferences

csinva/csinva

readme

csinva/matrix-completion-llm

Training LLMs for matrix completion

csinva/awesome-llm-interpretability

A curated list of Large Language Model (LLM) Interpretability resources.

csinva/context-review

csinva/gam-experiments

csinva/llm-guided-data-explanation

Explaining data to humans with linear models + LLM hints.

csinva/r2d3-decision-tree

A clone of the animated decision tree at http://www.r2d3.us/ in React, React-Motion, and d3

csinva/tabpfn-v2-finetune

Code for finetuning TabPFN on one downstream tabular dataset.