Alternatives and similar repositories for ShapleyExplanationNetworks:

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

• changliu00 / causal-semantic-generative-model
  Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution …
  ☆73Updated 2 years ago
• CAMP-eXplain-AI / InputIBA
  NeurIPS 2021 | Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information
  ☆32Updated 3 years ago
• TongtongFANG / DIW
  Code for the paper "Rethinking Importance Weighting for Deep Learning under Distribution Shift".
  ☆27Updated 3 years ago
• siplab-gt / generative-causal-explanations
  Code for "Generative causal explanations of black-box classifiers"
  ☆33Updated 4 years ago
• dylan-slack / Modeling-Uncertainty-Local-Explainability
  Local explanations with uncertainty 💐!
  ☆39Updated last year
• maksym33 / FeatureImportanceDL
  ☆41Updated last year
• amiratag / DistributionalShapley
  Distributional Shapley: A Distributional Framework for Data Valuation
  ☆30Updated 8 months ago
• ynysjtu / ood_bench
  ☆48Updated 2 years ago
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆48Updated 3 years ago
• ahujak / IB-IRM
  ☆30Updated 3 years ago
• iancovert / fastshap
  An amortized approach for calculating local Shapley value explanations
  ☆94Updated last year
• CVxTz / IntegratedGradientsPytorch
  Integrated gradients attribution method implemented in PyTorch
  ☆25Updated 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 last year
• microsoft / robustdg
  Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.
  ☆175Updated last year
• sudiptodip15 / CCMI
  Classifier based mutual information, conditional mutual information estimation; conditional independence testing
  ☆34Updated 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…
  ☆73Updated 7 years ago
• csinva / hierarchical-dnn-interpretations
  Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
  ☆128Updated 3 years ago
• huaxiuyao / C-Mixup
  C-Mixup for NeurIPS 2022
  ☆68Updated last year
• kohpangwei / group-influence-release
  ☆50Updated last year
• huaxiuyao / Wild-Time
  Benchmark for Natural Temporal Distribution Shift (NeurIPS 2022)
  ☆65Updated last year
• p-lambda / gradual_domain_adaptation
  ☆35Updated 3 years ago
• iancovert / shapley-regression
  For calculating Shapley values via linear regression.
  ☆66Updated 3 years ago
• LJSthu / HRM
  The code for the paper 'Heterogeneous Risk Minimization' of ICML2021.
  ☆24Updated 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
• AmanDaVinci / SENN
  Self-Explaining Neural Networks
  ☆39Updated 4 years ago
• AI-secure / multi-task-learning
  Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation", Haoxi…
  ☆67Updated 3 years ago
• JunwenBai / MPVAE
  MPVAE: Multivariate Probit Variational AutoEncoder for Multi-Label Classification
  ☆31Updated 3 months ago
• uiuctml / ISR
  Invariant-feature Subspace Recovery (ISR)
  ☆23Updated 2 years ago
• boschresearch / hierarchical_anomaly_detection
  Implementation of the paper "Understanding anomaly detection with deep invertible networks through hierarchies of distributions and featu…
  ☆41Updated 4 years ago
• m-Just / OoD-Bench
  ☆42Updated 2 years ago