Alternatives and similar repositories for fastshap

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

• iancovert / shapley-regression
  For calculating Shapley values via linear regression.
  ☆68Updated 4 years ago
• mlfoundations / tableshift
  A benchmark for distribution shift in tabular data
  ☆53Updated last year
• dylan-slack / Modeling-Uncertainty-Local-Explainability
  Local explanations with uncertainty 💐!
  ☆40Updated last year
• opendataval / opendataval
  OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)
  ☆97Updated 4 months ago
• AIgen / df-posthoc-calibration
  Model-agnostic posthoc calibration without distributional assumptions
  ☆42Updated last year
• LevinRoman / tabular-transfer-learning
  A repo for transfer learning with deep tabular models
  ☆104Updated 2 years ago
• amiratag / DistributionalShapley
  Distributional Shapley: A Distributional Framework for Data Valuation
  ☆30Updated last year
• AmrMKayid / nam
  Neural Additive Models (Google Research)
  ☆70Updated 3 years ago
• MaheepChaudhary / Causality-in-Trustworthy-Machine-Learning
  The repository contains lists of papers on causality and how relevant techniques are being used to further enhance deep learning era comp…
  ☆93Updated last year
• ioanabica / Counterfactual-Recurrent-Network
  Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…
  ☆59Updated last year
• ModelOriented / metaMIMIC
  ☆12Updated 2 years ago
• ElementAI / causal_discovery_toolbox
  Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
  ☆30Updated 5 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
• andreArtelt / ceml
  CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox
  ☆44Updated 3 weeks ago
• zzzace2000 / nodegam
  Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"
  ☆47Updated 2 years ago
• divyat09 / cf-feasibility
  Code accompanying the paper "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"
  ☆31Updated 2 years ago
• sanatonek / time_series_explainability
  ☆61Updated 4 years ago
• facebookresearch / nbm-spam
  Training and evaluating NBM and SPAM for interpretable machine learning.
  ☆78Updated 2 years ago
• wangyongjie-ntu / CFAI
  A collection of algorithms of counterfactual explanations.
  ☆50Updated 4 years ago
• criteo-research / continuous-fairness
  ☆22Updated 6 years ago
• iancovert / sage
  For calculating global feature importance using Shapley values.
  ☆271Updated 2 weeks ago
• vanderschaarlab / MIRACLE
  ☆28Updated last year
• amber0309 / HSIC
  Python code of Hilbert-Schmidt Independence Criterion
  ☆87Updated 3 years ago
• charmlab / mace
  Model Agnostic Counterfactual Explanations
  ☆87Updated 2 years ago
• facebookresearch / infoshap
  Codebase for information theoretic shapley values to explain predictive uncertainty.This repo contains the code related to the paperWatso…
  ☆21Updated 11 months ago
• acmi-lab / PU_learning
  Code and results accompanying our paper titled Mixture Proportion Estimation and PU Learning: A Modern Approach at Neurips 2021 (Spotligh…
  ☆44Updated last year
• sjblim / rmsn_nips_2018
  ☆39Updated 6 years ago
• p-lambda / verified_calibration
  Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…
  ☆150Updated 2 years ago
• MLforHealth / ClinicalDG
  An Empirical Framework for Domain Generalization In Clinical Settings
  ☆30Updated 3 years ago
• inouye-lab / ShapleyExplanationNetworks
  Implementation of the paper "Shapley Explanation Networks"
  ☆88Updated 4 years ago