Alternatives and similar repositories for concept-based-xai:

Users that are interested in concept-based-xai are comparing it to the libraries listed below

• mateoespinosa / cem
  Repository for our NeurIPS 2022 paper "Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off" and our NeurIPS 2023 paper…
  ☆58Updated last month
• izmailovpavel / spurious_feature_learning
  ☆44Updated 2 years ago
• HazyResearch / hidden-stratification
  Combating hidden stratification with GEORGE
  ☆63Updated 3 years ago
• ema-marconato / glancenet
  Updated code base for GlanceNets: Interpretable, Leak-proof Concept-based models
  ☆25Updated last year
• ykwon0407 / beta_shapley
  Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)
  ☆40Updated 2 years ago
• MLforHealth / ClinicalDG
  An Empirical Framework for Domain Generalization In Clinical Settings
  ☆30Updated 2 years ago
• aniruddhraghu / meta-pretraining
  Code accompanying paper: Meta-Learning to Improve Pre-Training
  ☆37Updated 3 years ago
• mlfoundations / tableshift
  A benchmark for distribution shift in tabular data
  ☆50Updated 9 months ago
• asmadotgh / dissect
  DISSECT: Disentangled Simultaneous Explanations via Concept Traversals
  ☆11Updated last year
• cambridge-mlg / CLUE
  Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"
  ☆35Updated 10 months ago
• kakaobrain / irm-empirical-study
  An Empirical Study of Invariant Risk Minimization
  ☆27Updated 4 years ago
• dmitrykazhdan / CME
  CME: Concept-based Model Extraction
  ☆12Updated 4 years ago
• jlko / active-testing
  Active and Sample-Efficient Model Evaluation
  ☆24Updated 4 years ago
• kimjeyoung / SNGP-BERT-Pytorch
  This is reimplementation of "Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness" in Pyt…
  ☆48Updated 3 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
• pietrobarbiero / entropy-lens
  ☆16Updated 2 years ago
• huaxiuyao / LISA
  LISA for ICML 2022
  ☆47Updated last year
• jamestszhim / modals
  MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space
  ☆40Updated 4 years ago
• dilyabareeva / quanda
  A toolkit for quantitative evaluation of data attribution methods.
  ☆41Updated last week
• chihkuanyeh / concept_exp
  code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"
  ☆53Updated 2 years ago
• HazyResearch / model-patching
  Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
  ☆42Updated 4 years ago
• js-d / sim_metric
  ☆35Updated last year
• pietrobarbiero / logic_explained_networks
  Logic Explained Networks is a python repository implementing explainable-by-design deep learning models.
  ☆48Updated last year
• abacusai / xai-bench
  XAI-Bench is a library for benchmarking feature attribution explainability techniques
  ☆63Updated 2 years ago
• siplab-gt / generative-causal-explanations
  Code for "Generative causal explanations of black-box classifiers"
  ☆33Updated 4 years ago
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆41Updated last year
• AmrMKayid / nam
  Neural Additive Models (Google Research)
  ☆69Updated 3 years ago
• oscarkey / explanations-by-minimizing-uncertainty
  Code for "Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties"
  ☆18Updated 3 years ago
• MadryLab / DebuggableDeepNetworks
  ☆38Updated 3 years ago
• annahedstroem / MetaQuantus
  MetaQuantus is an XAI performance tool to identify reliable evaluation metrics
  ☆33Updated 11 months ago