x-y-zhao / BayLimeLinks
bayesian lime
β18Updated last year
Alternatives and similar repositories for BayLime
Users that are interested in BayLime are comparing it to the libraries listed below
Sorting:
- β18Updated 2 years ago
- Local explanations with uncertainty π!β40Updated 2 years ago
- General fair regression subject to demographic parity constraint. Paper appeared in ICML 2019.β16Updated 5 years ago
- Generate robust counterfactual explanations for machine learning modelsβ16Updated 2 years ago
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)β84Updated 2 years ago
- Efficient Computation and Analysis of Distributional Shapley Values (AISTATS 2021)β22Updated last year
- Github for the NIPS 2020 paper "Learning outside the black-box: at the pursuit of interpretable models"β15Updated 3 years ago
- Code for "Consistent Estimators for Learning to Defer to an Expert" (ICML 2020)β13Updated 2 years ago
- Model Agnostic Counterfactual Explanationsβ88Updated 3 years ago
- β16Updated 3 years ago
- XAI-Bench is a library for benchmarking feature attribution explainability techniquesβ70Updated 2 years ago
- A collection of algorithms of counterfactual explanations.β50Updated 4 years ago
- Model-agnostic posthoc calibration without distributional assumptionsβ42Updated last year
- code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"β53Updated 3 years ago
- Fair Empirical Risk Minimization (FERM)β37Updated 5 years ago
- A benchmark for distribution shift in tabular dataβ55Updated last year
- OpenXAI : Towards a Transparent Evaluation of Model Explanationsβ248Updated last year
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotligβ¦β151Updated 2 years ago
- Papers and code of Explainable AI esp. w.r.t. Image classificiationβ218Updated 3 years ago
- Reliability diagrams visualize whether a classifier model needs calibrationβ158Updated 3 years ago
- Reference tables to introduce and organize evaluation methods and measures for explainable machine learning systemsβ75Updated 3 years ago
- Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"β31Updated 2 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831β36Updated 2 years ago
- This repository contains the implementation of Label-Free XAI, a new framework to adapt explanation methods to unsupervised models. For mβ¦β23Updated 3 years ago
- β10Updated 3 years ago
- For calculating Shapley values via linear regression.β71Updated 4 years ago
- A fairness library in PyTorch.β30Updated last year
- Code repository for the AAAI 2022 paper "Do Feature Attribution Methods Correctly Attribute Features?"β20Updated 3 years ago
- Code for the paper "Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers" published in ICLR 2019β14Updated 6 years ago
- An amortized approach for calculating local Shapley value explanationsβ100Updated last year