alexeyignatiev / xreasonLinks
XReason - formal reasoning about explanations for ML models
☆17Updated 2 months ago
Alternatives and similar repositories for xreason
Users that are interested in xreason are comparing it to the libraries listed below
Sorting:
- Logic Explained Networks is a python repository implementing explainable-by-design deep learning models.☆50Updated 2 years ago
- Python package for Sentential Decision Diagrams (SDD)☆63Updated 4 months ago
- Explanation Optimization☆13Updated 4 years ago
- Codebase for VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming☆20Updated 2 years ago
- DL2 is a framework that allows training neural networks with logical constraints over numerical values in the network (e.g. inputs, out…☆86Updated 11 months ago
- A Library for Minimax Risk Classifiers☆31Updated last year
- Tensorflow implementation for the Class-wise Selective Rationalization☆14Updated 2 years ago
- A new framework to generate interpretable classification rules☆17Updated 2 years ago
- Model Agnostic Counterfactual Explanations☆87Updated 2 years ago
- ☆32Updated 3 years ago
- Manipulate NNF (Negation Normal Form) logical sentences☆18Updated 2 years ago
- ☆10Updated 3 years ago
- Fair Empirical Risk Minimization (FERM)☆37Updated 4 years ago
- Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI☆55Updated 2 years ago
- csl: PyTorch-based Constrained Learning☆12Updated 3 years ago
- This repository holds the code for the NeurIPS 2022 paper, Semantic Probabilistic Layers☆30Updated last year
- The Python PSDD Package☆17Updated last month
- Code for paper "Search Methods for Sufficient, Socially-Aligned Feature Importance Explanations with In-Distribution Counterfactuals"☆18Updated 2 years ago
- 👋 Code for the paper: "Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis" (NeurIPS 2021)☆30Updated 2 years ago
- ☆12Updated 2 years ago
- ☆46Updated last year
- MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".☆18Updated 2 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆36Updated 2 years ago
- Github for the NIPS 2020 paper "Learning outside the black-box: at the pursuit of interpretable models"☆15Updated 2 years ago
- ☆11Updated 2 years ago
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)☆82Updated 2 years ago
- Self-Explaining Neural Networks☆42Updated 5 years ago
- Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"☆31Updated 2 years ago
- XAI-Bench is a library for benchmarking feature attribution explainability techniques☆69Updated 2 years ago
- A collection of commonly used datasets as benchmarks for density estimation☆24Updated 5 years ago