epfl-ml4ed / evaluating-explainersLinks
Comparing 5 different XAI techniques (LIME, PermSHAP, KernelSHAP, DiCE, CEM) through quantitative metrics. Published at EDM 2022.
☆17Updated 3 years ago
Alternatives and similar repositories for evaluating-explainers
Users that are interested in evaluating-explainers are comparing it to the libraries listed below
Sorting:
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆252Updated last year
- For calculating Shapley values via linear regression.☆73Updated 4 years ago
- Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations☆636Updated 2 weeks ago
- Repository for "The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications"☆11Updated 8 months ago
- Rule Extraction Methods for Interactive eXplainability☆48Updated 3 years ago
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)☆85Updated 3 years ago
- Neural Additive Models (Google Research)☆31Updated last year
- Estimators for the entropy and other information theoretic quantities of continuous distributions☆146Updated last year
- For calculating global feature importance using Shapley values.☆284Updated last week
- Generate robust counterfactual explanations for machine learning models☆16Updated 2 years ago
- Neural Additive Models (Google Research)☆74Updated 4 years ago
- Tensorflow 2.1 implementation of LRP for LSTMs☆40Updated 3 years ago
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆84Updated last year
- Python automated machine learning framework.☆34Updated 2 months ago
- TimeSHAP explains Recurrent Neural Network predictions.☆196Updated 2 years ago
- ShapleyVIC: Shapley Variable Importance Cloud for Interpretable Machine Learning☆20Updated last year
- ☆10Updated 2 years ago
- Generalized Optimal Sparse Decision Trees☆60Updated 8 months ago
- pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation☆142Updated 3 weeks ago
- (Conditional) Independence testing & Markov blanket feature selection using k-NN mutual information and conditional mutual information es…☆31Updated 5 years ago
- A collection of algorithms of counterfactual explanations.☆52Updated 4 years ago
- This repository provides details of the experimental code in the paper: Instance-based Counterfactual Explanations for Time Series Classi…☆22Updated 4 years ago
- ☆49Updated 2 years ago
- pyCausalFS:A Python Library of Causality-based Feature Selection for Causal Structure Learning and Classification☆71Updated 5 years ago
- Overview of different model interpretability libraries.☆51Updated 3 years ago
- Causal Learner: A Toolbox for Causal Structure and Markov Blanket Learning☆43Updated 11 months ago
- An amortized approach for calculating local Shapley value explanations☆105Updated 2 years ago
- Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"☆47Updated 3 years ago
- An Open-Source Library for the interpretability of time series classifiers☆144Updated 2 months ago
- A fairness library in PyTorch.☆32Updated last year