Stars
Difference-in-Differences causal inference in Python. Callaway-Sant'Anna, Synthetic DiD, Honest DiD, event studies. sklearn-like API, validated against R.
A self-hosted web terminal for Claude Code with multi-user authenticated access, accessible from any browser.
This is the repository for the Python library mlsynth
A Python package for causal inference in quasi-experimental settings
Synthetic difference in differences for Python
Examples of PyMC models, including a library of Jupyter notebooks.
Topics in Advanced Econometrics (ResEcon 703). University of Massachusetts Amherst. Taught by Matt Woerman
This repository contains demos I made with the Transformers library by HuggingFace.
Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"
[NeurIPS 2021] Multiscale Benchmarks for Multimodal Representation Learning
The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy
R package for causal machine learning for segment discovery and analysis
High dimensional fixed effect absorption with Python 3
Homework assignments to go along with The Effect
Materials to reproduce our findings in our stories, "Amazon Puts Its Own 'Brands' First Above Better-Rated Products" and "When Amazon Takes the Buy Box, it Doesn’t Give it up"
A Python library to access Instagram's private API.
Pytorch code for TM-GCN, a Dynamic Graph Convolutional Networks Using the Tensor M-Product
LeViT a Vision Transformer in ConvNet's Clothing for Faster Inference
A collection of reference Jupyter notebooks and demo AI/ML applications for enterprise use cases: marketing, pricing, supply chain, smart manufacturing, and more.
Paper