csinva

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

Scikit-learn friendly library to interpret, and prompt-engineer text datasets using large language models.

iprompt

Finding semantically meaningful and accurate prompts.

tree-prompt

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

deep-explanation-penalization

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

covid19-severity-prediction

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

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/imodelsX

Scikit-learn friendly library to interpret, and prompt-engineer text datasets using large language models.

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/tree-prompt

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

csinva/interpretable-embeddings

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

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/iai-clinical-decision-rule

Interpretable clinical decision rules for predicting intra-abdominal injury.

csinva/clinical-rule-analysis

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

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/tree-prompt-experiments

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

csinva/acronym-generator

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

csinva/fmri

Experiments with language fMRI data from Alex Huth lab

csinva/tpr-fmri

csinva/inverse-scaling

A prize for finding tasks that cause large language models to show inverse scaling

csinva/news-title-bias

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

csinva/csinva

readme

csinva/matrix-completion-llm

Training LLMs for matrix completion

csinva/pedidose-efic-analysis

Analyzing interview data from the PediDOSE EFIC interviews using LLMs.

csinva/pyGAM

[HELP REQUESTED] Generalized Additive Models in Python

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