iancovert / fastshap
An amortized approach for calculating local Shapley value explanations
β97Updated last year
Alternatives and similar repositories for fastshap:
Users that are interested in fastshap are comparing it to the libraries listed below
- For calculating Shapley values via linear regression.β67Updated 3 years ago
- Local explanations with uncertainty π!β39Updated last year
- A benchmark for distribution shift in tabular dataβ50Updated 9 months ago
- Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"β43Updated 2 years ago
- Neural Additive Models (Google Research)β69Updated 3 years ago
- A repo for transfer learning with deep tabular modelsβ102Updated 2 years ago
- Repository for our NeurIPS 2022 paper "Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off" and our NeurIPS 2023 paperβ¦β58Updated last month
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.β130Updated 4 years ago
- OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)β95Updated last month
- Model-agnostic posthoc calibration without distributional assumptionsβ42Updated last year
- XAI-Bench is a library for benchmarking feature attribution explainability techniquesβ63Updated 2 years ago
- For calculating global feature importance using Shapley values.β266Updated this week
- OpenXAI : Towards a Transparent Evaluation of Model Explanationsβ239Updated 7 months ago
- Distributional Shapley: A Distributional Framework for Data Valuationβ30Updated 10 months ago
- Introduction, selected papers and possible corresponding codes in our review paper "A Survey of Neural Trees"β79Updated 2 years ago
- β12Updated 2 years ago
- A curated list of papers and resources about the distribution shift in machine learning.β111Updated last year
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"β35Updated 10 months ago
- Implementation of the paper "Shapley Explanation Networks"β88Updated 4 years ago
- General fair regression subject to demographic parity constraint. Paper appeared in ICML 2019.β15Updated 4 years ago
- The repository contains lists of papers on causality and how relevant techniques are being used to further enhance deep learning era compβ¦β91Updated last year
- Training and evaluating NBM and SPAM for interpretable machine learning.β77Updated last year
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.β30Updated 5 years ago
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)β82Updated 2 years ago
- NumPy library for calibration metricsβ69Updated 3 weeks ago
- Beta calibrationβ29Updated last year
- Model Agnostic Counterfactual Explanationsβ87Updated 2 years ago
- Neural Additive Models (Google Research)β26Updated 10 months ago
- A lightweight implementation of removal-based explanations for ML models.β59Updated 3 years ago
- An Empirical Framework for Domain Generalization In Clinical Settingsβ30Updated 2 years ago