divyat09 / cf-feasibilityLinks
Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"
☆31Updated 2 years ago
Alternatives and similar repositories for cf-feasibility
Users that are interested in cf-feasibility are comparing it to the libraries listed below
Sorting:
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆36Updated 2 years ago
- Model Agnostic Counterfactual Explanations☆87Updated 2 years ago
- A collection of algorithms of counterfactual explanations.☆50Updated 4 years ago
- Distributional Shapley: A Distributional Framework for Data Valuation☆30Updated last year
- Code for "Generative causal explanations of black-box classifiers"☆34Updated 4 years ago
- Local explanations with uncertainty 💐!☆40Updated last year
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 3 years ago
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆30Updated 5 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆41Updated 2 years ago
- ☆50Updated 2 years ago
- GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model’s Prediction. Thai Le, Suhang Wang, Dongwon …☆21Updated 4 years ago
- CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox☆44Updated this week
- ☆32Updated 6 years ago
- An Empirical Framework for Domain Generalization In Clinical Settings☆30Updated 3 years ago
- Self-Explaining Neural Networks☆42Updated 5 years ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆35Updated last year
- Codes for reproducing the contrastive explanation in “Explanations based on the Missing: Towards Contrastive Explanations with Pertinent…☆54Updated 6 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆52Updated 4 years ago
- Self-Explaining Neural Networks☆13Updated last year
- 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
- code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"☆53Updated 3 years ago
- Python implementation of the Invariant Causal Prediction (ICP) algorithm, from the 2015 paper "Causal inference using invariant predictio…☆22Updated last year
- A benchmark for distribution shift in tabular data☆52Updated 11 months ago
- ☆16Updated 3 years ago
- Code for "Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties"☆18Updated 4 years ago
- Fair Empirical Risk Minimization (FERM)☆37Updated 4 years ago
- Code/figures in Right for the Right Reasons☆55Updated 4 years ago
- Code and data for the experiments in "On Fairness and Calibration"☆51Updated 3 years ago
- Implementation of Minimax Pareto Fairness framework☆21Updated 4 years ago
- Code for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. …☆52Updated 4 years ago