Alternatives and similar repositories for explanations-by-minimizing-uncertainty:

Users that are interested in explanations-by-minimizing-uncertainty are comparing it to the libraries listed below

• dylan-slack / Modeling-Uncertainty-Local-Explainability
  Local explanations with uncertainty 💐!
  ☆40Updated last year
• dmelis / SENN
  Self-Explaining Neural Networks
  ☆13Updated last year
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆42Updated last year
• vislearn / GIN
  Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)
  ☆32Updated 3 years ago
• siplab-gt / generative-causal-explanations
  Code for "Generative causal explanations of black-box classifiers"
  ☆34Updated 4 years ago
• charan223 / FairDeepLearning
  ☆37Updated 2 years ago
• sharpenb / Posterior-Network
  Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)
  ☆76Updated 2 years ago
• cambridge-mlg / CLUE
  Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"
  ☆35Updated last year
• YyzHarry / SubpopBench
  [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift
  ☆108Updated last year
• mlfoundations / tableshift
  A benchmark for distribution shift in tabular data
  ☆52Updated 11 months ago
• capybaralet / REx_code_release
  ☆64Updated 4 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
• nickruggeri / CLAP-interpretable-predictions
  Official codebase for the paper "Provable concept learning for interpretable predictions using variational inference".
  ☆14Updated 3 years ago
• pietrobarbiero / entropy-lens
  ☆16Updated 2 years ago
• AmanDaVinci / SENN
  Self-Explaining Neural Networks
  ☆42Updated 5 years ago
• aniruddhraghu / meta-pretraining
  Code accompanying paper: Meta-Learning to Improve Pre-Training
  ☆37Updated 3 years ago
• xwshen51 / DEAR
  Disentangled gEnerative cAusal Representation (DEAR)
  ☆60Updated 2 years ago
• ysharma1126 / ssl_identifiability
  Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
  ☆51Updated 3 years ago
• namratadeka / circe
  Efficient Conditionally Invariant Representation Learning (ICLR 2023, Oral)
  ☆21Updated 2 years ago
• siamakz / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆47Updated 5 years ago
• slachapelle / disentanglement_via_mechanism_sparsity
  ☆17Updated last year
• divyat09 / cf-feasibility
  Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"
  ☆31Updated 2 years ago
• izmailovpavel / spurious_feature_learning
  ☆45Updated 2 years ago
• ServiceNow / beyond-trivial-explanations
  Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations is a ServiceNow Research project that was started at Elemen…
  ☆13Updated last year
• dmitrykazhdan / concept-based-xai
  Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI
  ☆54Updated 2 years ago
• facebookresearch / CausalRepID
  Experiments to reproduce results in Interventional Causal Representation Learning.
  ☆24Updated 2 years ago
• navid-naderi / WEGL
  The implementation code for our paper Wasserstein Embedding for Graph Learning (ICLR 2021).
  ☆35Updated 4 years ago
• criteo-research / continuous-fairness
  ☆22Updated 5 years ago
• HongtengXu / Relational-AutoEncoders
  Learning Autoencoders with Relational Regularization
  ☆46Updated 4 years ago
• IBM / OoD
  Repository for theory and methods for Out-of-Distribution (OoD) generalization
  ☆63Updated 3 years ago