Alternatives and similar repositories for InputIBA

Users that are interested in InputIBA are comparing it to the libraries listed below

• YyzHarry / SubpopBench
  [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift
  ☆111Updated 2 years ago
• IBM / concept_transformer
  Code for the ICLR 2022 paper "Attention-based interpretability with Concept Transformers"
  ☆42Updated 4 months ago
• zju-vipa / ProtoPFormer
  ProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition
  ☆40Updated 3 years ago
• BioroboticsLab / IBA
  Information Bottlenecks for Attribution
  ☆84Updated 3 years ago
• izmailovpavel / spurious_feature_learning
  ☆47Updated 3 years ago
• zengyi-li / NMCE-release
  Code for Neural Manifold Clustering and Embedding
  ☆62Updated 3 years ago
• omegafragger / DDU
  Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty
  ☆147Updated 2 years ago
• IML-DKFZ / fd-shifts
  A Benchmark for Failure Detection under Distribution Shifts in Image Classification
  ☆35Updated last year
• zhiCHEN96 / ConceptWhitening
  ☆122Updated 3 years ago
• belaalb / G2DM
  Generalizing to unseen domains via distribution matching
  ☆73Updated 5 years ago
• zhang64-llnl / Mix-n-Match-Calibration
  ☆38Updated 5 years ago
• google-deepmind / distribution_shift_framework
  This repository contains the code of the distribution shift framework presented in A Fine-Grained Analysis on Distribution Shift (Wiles e…
  ☆86Updated 3 weeks ago
• huaxiuyao / LISA
  LISA for ICML 2022
  ☆52Updated 2 years ago
• ryoungj / optdom
  [ICLR'22] Self-supervised learning optimally robust representations for domain shift.
  ☆25Updated 3 years ago
• sungyubkim / MCDO
  A pytorch implementation of MCDO(Monte-Carlo Dropout methods)
  ☆58Updated 7 years ago
• Jonathan-Pearce / calibration-toolbox
  NumPy library for calibration metrics
  ☆75Updated 2 weeks ago
• bat-sheva / Conformal-Learning
  ☆25Updated 3 years ago
• microsoft / robustdg
  Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.
  ☆175Updated 2 years ago
• YugeTen / fish
  Official implementation of paper Gradient Matching for Domain Generalization
  ☆124Updated 4 years ago
• arobey1 / mbdg
  ☆36Updated 4 years ago
• torrvision / focal_calibration
  Code for the paper "Calibrating Deep Neural Networks using Focal Loss"
  ☆161Updated 2 years ago
• alexrame / fishr
  Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization
  ☆89Updated 3 years ago
• ysharma1126 / ssl_identifiability
  Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
  ☆54Updated 4 years ago
• KaosEngineer / PriorNetworks
  ☆68Updated 6 years ago
• yewsiang / ConceptBottleneck
  Concept Bottleneck Models, ICML 2020
  ☆237Updated 2 years ago
• valentyn1boreiko / DVCEs
  ☆44Updated last year
• bethgelab / robustness
  Robustness and adaptation of ImageNet scale models. Pre-Release, stay tuned for updates.
  ☆137Updated 2 years ago
• mateoespinosa / cem
  Repository for our NeurIPS 2022 paper "Concept Embedding Models", our NeurIPS 2023 paper "Learning to Receive Help", and our ICML 2025 pa…
  ☆72Updated this week
• daintlab / confidence-aware-learning
  Confidence-Aware Learning for Deep Neural Networks (ICML2020)
  ☆74Updated 5 years ago
• somepago / dbViz
  The official PyTorch implementation - Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from t…
  ☆83Updated 3 years ago