Alternatives and similar repositories for h-shap

Users that are interested in h-shap are comparing it to the libraries listed below

• facebookresearch / nbm-spam
  Training and evaluating NBM and SPAM for interpretable machine learning.
  ☆78Updated 2 years ago
• clementchadebec / pyraug
  Data Augmentation with Variational Autoencoders (TPAMI)
  ☆142Updated 3 years ago
• google-deepmind / conformal_training
  This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…
  ☆130Updated 3 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
• scikit-learn-contrib / scikit-dimension
  A Python package for intrinsic dimension estimation
  ☆93Updated this week
• aangelopoulos / conformal-risk
  Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…
  ☆67Updated 2 years ago
• aangelopoulos / rcps
  Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"
  ☆85Updated last year
• adrianjav / heterogeneous_vaes
  Pytorch implementation of VAEs for heterogeneous likelihoods.
  ☆42Updated 2 years ago
• ema-marconato / glancenet
  Updated code base for GlanceNets: Interpretable, Leak-proof Concept-based models
  ☆25Updated 2 years ago
• jmkuebler / auto-tst
  AutoML Two-Sample Test
  ☆20Updated 3 years ago
• AmrMKayid / nam
  Neural Additive Models (Google Research)
  ☆71Updated 3 years ago
• BlackHC / batchbald_redux
  Reusable BatchBALD implementation
  ☆79Updated last year
• MLforHealth / ClinicalDG
  An Empirical Framework for Domain Generalization In Clinical Settings
  ☆30Updated 3 years ago
• dmitrykazhdan / concept-based-xai
  Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI
  ☆54Updated 3 years ago
• runame / laplace-redux
  Laplace Redux -- Effortless Bayesian Deep Learning
  ☆42Updated 3 months ago
• aniruddhraghu / meta-pretraining
  Code accompanying paper: Meta-Learning to Improve Pre-Training
  ☆37Updated 3 years ago
• abacusai / xai-bench
  XAI-Bench is a library for benchmarking feature attribution explainability techniques
  ☆70Updated 2 years ago
• AIgen / df-posthoc-calibration
  Model-agnostic posthoc calibration without distributional assumptions
  ☆42Updated last year
• MadryLab / modeldiff
  ModelDiff: A Framework for Comparing Learning Algorithms
  ☆59Updated 2 years ago
• mlhcmit / edx-materials
  Contains public materials for students enrolled in MITx: 6.871x, Machine Learning for Healthcare
  ☆20Updated 4 years ago
• bmucsanyi / untangle
  Large-scale uncertainty benchmark in deep learning.
  ☆63Updated 4 months ago
• hsouri / BayesianTransferLearning
  ☆108Updated 2 years ago
• probabilisticai / probai-2023
  Materials of the Nordic Probabilistic AI School 2023.
  ☆90Updated last year
• rajesh-lab / deep_permutation_invariant
  Code accompanying paper "Set Norm and Equivariant Skip Connections: Putting the Deep in Deep Sets."
  ☆28Updated 2 years ago
• Pacmed / ehr_ood_detection
  Pacmed Labs experiments on uncertainty estimation, focusing on unbalanced tabular data and classification tasks.
  ☆21Updated 4 years ago
• ahmedmalaa / Symbolic-Metamodeling
  Codebase for "Demystifying Black-box Models with Symbolic Metamodels", NeurIPS 2019.
  ☆51Updated 5 years ago
• TorchUQ / torchuq
  A library for uncertainty quantification based on PyTorch
  ☆122Updated 3 years ago
• ykwon0407 / fast_dist_shapley
  Efficient Computation and Analysis of Distributional Shapley Values (AISTATS 2021)
  ☆22Updated last year
• aangelopoulos / private_prediction_sets
  Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.
  ☆18Updated last year
• jlko / active-testing
  Active and Sample-Efficient Model Evaluation
  ☆24Updated 3 months ago