Popular GitHub Repositories for Counterfactual Regret

Algorithms for explaining machine learning models

? An Open Source Texas Hold'em AI

Auton Survival - an open source package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Events

? Adversarial attacks on explanations and how to defend them

Scalable Implementation of Deep CFR and Single Deep CFR

A pytorch tutorial for DRL(Deep Reinforcement Learning)

Play, learn, solve, and analyze No-Limit Texas Hold Em. Implementation follows from Monte Carlo counter-factual regret minimization over with hierarchical K-means imperfect recall abstractions.

?? Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.

FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)

Author: Tong Zhao (tzhao2@nd.edu). ICML 2022. Learning from Counterfactual Links for Link Prediction

RF-Next: Efficient Receptive Field Search for CNN(TPAMI2022, CVPR2021) Try it, you wouldn't regret it!

(ICML 2023) High Fidelity Image Counterfactuals with Probabilistic Causal Models

PyTorch implementation of Foerster, Jakob N., et al. "Counterfactual multi-agent policy gradients."

A list of research papers of explainable machine learning.

Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"

cfrx is a collection of algorithms and tools for hardware-accelerated Counterfactual Regret Minimization (CFR) algorithms in Jax.

(ICML2020) “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models’’

Counterfactual Local Explanations of AI systems

PyTorch implementation for our proposed CFIE in EMNLP 2021 paper "Uncovering Main Causalities for Long-tailed Information Extraction".