Alternatives and similar repositories for fast_dist_shapley

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

• ykwon0407 / beta_shapley
  Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)
  ☆41Updated 2 years ago
• amiratag / DistributionalShapley
  Distributional Shapley: A Distributional Framework for Data Valuation
  ☆30Updated last year
• opendataval / opendataval
  OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)
  ☆99Updated 6 months ago
• dylan-slack / Modeling-Uncertainty-Local-Explainability
  Local explanations with uncertainty 💐!
  ☆40Updated 2 years ago
• mlfoundations / tableshift
  A benchmark for distribution shift in tabular data
  ☆55Updated last year
• MLforHealth / ClinicalDG
  An Empirical Framework for Domain Generalization In Clinical Settings
  ☆31Updated 3 years ago
• ykwon0407 / wdro_local_perturbation
  Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)
  ☆21Updated 2 years ago
• ykwon0407 / dataoob
  Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value (ICML 2023)
  ☆19Updated 2 years ago
• jjbrophy47 / tree_influence
  Influence Estimation for Gradient-Boosted Decision Trees
  ☆30Updated last year
• BlackHC / batchbald_redux
  Reusable BatchBALD implementation
  ☆79Updated last year
• jmikko / fair_ERM
  Fair Empirical Risk Minimization (FERM)
  ☆37Updated 4 years ago
• dh7401 / T-Cal
  ☆10Updated 3 years ago
• kohpangwei / group-influence-release
  ☆50Updated 2 years ago
• a-lucic / focus
  ☆16Updated 3 years ago
• steven7woo / fair_regression_reduction
  General fair regression subject to demographic parity constraint. Paper appeared in ICML 2019.
  ☆16Updated 5 years ago
• LevinRoman / tabular-transfer-learning
  A repo for transfer learning with deep tabular models
  ☆104Updated 2 years ago
• AmrMKayid / nam
  Neural Additive Models (Google Research)
  ☆71Updated 3 years ago
• izmailovpavel / spurious_feature_learning
  ☆46Updated 2 years ago
• AmanDaVinci / SENN
  Self-Explaining Neural Networks
  ☆42Updated 5 years ago
• dmitrykazhdan / concept-based-xai
  Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI
  ☆55Updated 3 years ago
• siplab-gt / generative-causal-explanations
  Code for "Generative causal explanations of black-box classifiers"
  ☆35Updated 4 years ago
• charmlab / recourse
  Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831
  ☆36Updated 2 years ago
• iancovert / removal-explanations
  A lightweight implementation of removal-based explanations for ML models.
  ☆58Updated 4 years ago
• cambridge-mlg / CLUE
  Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"
  ☆36Updated last year
• aangelopoulos / ltt
  Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
  ☆68Updated 9 months ago
• vanderschaarlab / DECAF
  DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks
  ☆21Updated 2 months ago
• acmi-lab / cmu-10732-robustness-adaptivity-shift
  Official repository for CMU Machine Learning Department's 10732: Robustness and Adaptivity in Shifting Environments
  ☆74Updated 2 years ago
• ZaydH / influence_analysis_papers
  Influence Analysis and Estimation - Survey, Papers, and Taxonomy
  ☆82Updated last year
• mymakar / causally_motivated_shortcut_removal
  ☆15Updated 2 years ago
• jsyoon0823 / INVASE
  Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR
  ☆62Updated 5 years ago