MartinPawel / c-chvaeLinks
β11Updated 4 years ago
Alternatives and similar repositories for c-chvae
Users that are interested in c-chvae are comparing it to the libraries listed below
Sorting:
- Model Agnostic Counterfactual Explanationsβ87Updated 2 years ago
- Local explanations with uncertainty π!β40Updated last year
- Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"β31Updated 2 years ago
- This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help β¦β24Updated 2 years ago
- Fair Empirical Risk Minimization (FERM)β37Updated 4 years ago
- A collection of algorithms of counterfactual explanations.β50Updated 4 years ago
- bayesian limeβ17Updated 10 months ago
- A lightweight implementation of removal-based explanations for ML models.β59Updated 3 years ago
- A repo for transfer learning with deep tabular modelsβ104Updated 2 years ago
- XAI-Bench is a library for benchmarking feature attribution explainability techniquesβ68Updated 2 years ago
- A benchmark for distribution shift in tabular dataβ53Updated last year
- Invariant-feature Subspace Recovery (ISR)β23Updated 2 years ago
- An amortized approach for calculating local Shapley value explanationsβ99Updated last year
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)β82Updated 2 years ago
- Python package to compute interaction indices that extend the Shapley Value. AISTATS 2023.β17Updated last year
- code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"β53Updated 3 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831β36Updated 2 years ago
- [NeurIPS 2019] H. Chen*, H. Zhang*, S. Si, Y. Li, D. Boning and C.-J. Hsieh, Robustness Verification of Tree-based Models (*equal contribβ¦β27Updated 6 years ago
- For calculating Shapley values via linear regression.β68Updated 4 years ago
- Self-Explaining Neural Networksβ42Updated 5 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)β41Updated 2 years ago
- Code for "Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties"β18Updated 4 years ago
- Code for "Generative causal explanations of black-box classifiers"β34Updated 4 years ago
- Python implementation for evaluating explanations presented in "On the (In)fidelity and Sensitivity for Explanations" in NeurIPS 2019 forβ¦β25Updated 3 years ago
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Controlβ66Updated 7 months ago
- Active and Sample-Efficient Model Evaluationβ24Updated last month
- β21Updated 2 years ago
- Influence Estimation for Gradient-Boosted Decision Treesβ27Updated last year
- Code for paper: Are Large Language Models Post Hoc Explainers?β33Updated 11 months ago
- Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"β47Updated 2 years ago