Alternatives and similar repositories for cf-feasibility

Users that are interested in cf-feasibility are comparing it to the libraries listed below

• wangyongjie-ntu / CFAI
  A collection of algorithms of counterfactual explanations.
  ☆50Updated 4 years ago
• charmlab / recourse
  Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831
  ☆36Updated 2 years ago
• amiratag / DistributionalShapley
  Distributional Shapley: A Distributional Framework for Data Valuation
  ☆30Updated last year
• charmlab / mace
  Model Agnostic Counterfactual Explanations
  ☆87Updated 2 years ago
• Piyushi-0 / ACE
  Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.
  ☆51Updated 3 years ago
• siplab-gt / generative-causal-explanations
  Code for "Generative causal explanations of black-box classifiers"
  ☆34Updated 4 years ago
• jmikko / fair_ERM
  Fair Empirical Risk Minimization (FERM)
  ☆37Updated 4 years ago
• dylan-slack / Modeling-Uncertainty-Local-Explainability
  Local explanations with uncertainty 💐!
  ☆40Updated last year
• ElementAI / causal_discovery_toolbox
  Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
  ☆31Updated 5 years ago
• kohpangwei / group-influence-release
  ☆50Updated 2 years ago
• AmanDaVinci / SENN
  Self-Explaining Neural Networks
  ☆42Updated 5 years ago
• ykwon0407 / beta_shapley
  Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)
  ☆41Updated 2 years ago
• lethaiq / GRACE_KDD20
  GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model’s Prediction. Thai Le, Suhang Wang, Dongwon …
  ☆21Updated 4 years ago
• iancovert / removal-explanations
  A lightweight implementation of removal-based explanations for ML models.
  ☆59Updated 3 years ago
• sfme / RVAE_MixedTypes
  Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)
  ☆50Updated 5 years ago
• OscarcarLi / PrototypeDL
  Codebase for "Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains Its Predictions" (to appear in AA…
  ☆75Updated 7 years ago
• dtak / rrr
  Code/figures in Right for the Right Reasons
  ☆55Updated 4 years ago
• inouye-lab / ShapleyExplanationNetworks
  Implementation of the paper "Shapley Explanation Networks"
  ☆88Updated 4 years ago
• GDPlumb / MAPLE
  Supervised Local Modeling for Interpretability
  ☆29Updated 6 years ago
• MLforHealth / ClinicalDG
  An Empirical Framework for Domain Generalization In Clinical Settings
  ☆30Updated 3 years ago
• Jianbo-Lab / L2X
  ☆124Updated 4 years ago
• zzzace2000 / GAMs
  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
• natalialmg / MMPF
  Implementation of Minimax Pareto Fairness framework
  ☆21Updated 4 years ago
• sjblim / rmsn_nips_2018
  ☆39Updated 6 years ago
• andreArtelt / ceml
  CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox
  ☆44Updated 3 weeks ago
• a-lucic / focus
  ☆16Updated 3 years ago
• dylan-slack / Fooling-LIME-SHAP
  Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)
  ☆82Updated 2 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 6 years ago
• JonathanCrabbe / Simplex
  This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help …
  ☆24Updated 2 years ago
• diviyank / SAM
  Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)
  ☆52Updated 4 years ago