wangyongjie-ntu / CFAI
A collection of algorithms of counterfactual explanations.
☆50Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for CFAI
- CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox☆42Updated 3 months ago
- Model Agnostic Counterfactual Explanations☆87Updated 2 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆35Updated last year
- Local explanations with uncertainty 💐!☆39Updated last year
- XAI-Bench is a library for benchmarking feature attribution explainability techniques☆57Updated last year
- Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"☆30Updated last year
- Neural Additive Models (Google Research)☆67Updated 3 years ago
- This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help …☆24Updated last year
- Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"☆43Updated 2 years ago
- Efficient Computation and Analysis of Distributional Shapley Values (AISTATS 2021)☆21Updated last year
- For calculating Shapley values via linear regression.☆66Updated 3 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆40Updated 2 years ago
- A lightweight implementation of removal-based explanations for ML models.☆57Updated 3 years ago
- Code and data for decision making under strategic behavior, NeurIPS 2020 & Management Science 2024.☆27Updated 8 months ago
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆60Updated last year
- An amortized approach for calculating local Shapley value explanations☆92Updated 11 months ago
- Distributional Shapley: A Distributional Framework for Data Valuation☆30Updated 6 months ago
- Codebase for "Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions", ICML 2020.☆8Updated 4 years ago
- Code for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. …☆51Updated 3 years ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆80Updated 7 months ago
- Multi-Objective Counterfactuals☆40Updated 2 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆68Updated 3 years ago
- Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)☆50Updated 4 years ago
- A Natural Language Interface to Explainable Boosting Machines☆60Updated 4 months ago
- Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)☆25Updated 2 years ago
- Multiple Generalized Additive Models implemented in Python (EBM, XGB, Spline, FLAM). Code for our KDD 2021 paper "How Interpretable and T…☆12Updated 3 years ago
- OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)☆88Updated 3 months ago
- A benchmark for distribution shift in tabular data☆44Updated 5 months ago
- Code for "Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties"☆18Updated 3 years ago
- Influence Estimation for Gradient-Boosted Decision Trees☆25Updated 5 months ago