Sulam-Group / h-shapLinks
h-Shap provides an exact, fast, hierarchical implementation of Shapley coefficients for image explanations
☆16Updated 2 years ago
Alternatives and similar repositories for h-shap
Users that are interested in h-shap are comparing it to the libraries listed below
Sorting:
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer vi…☆72Updated 2 years ago
- Data Augmentation with Variational Autoencoders (TPAMI)☆143Updated 3 years ago
- An Empirical Framework for Domain Generalization In Clinical Settings☆30Updated 3 years ago
- A Python package for intrinsic dimension estimation☆94Updated 2 months ago
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classi…☆130Updated 3 years ago
- Training and evaluating NBM and SPAM for interpretable machine learning.☆78Updated 2 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆42Updated 3 years ago
- Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI☆54Updated 3 years ago
- Neural Additive Models (Google Research)☆73Updated 4 years ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"☆87Updated last year
- A lightweight implementation of removal-based explanations for ML models.☆59Updated 4 years ago
- 👋 Code for the paper: "Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis" (NeurIPS 2021)☆31Updated 3 years ago
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control☆70Updated last year
- Contains public materials for students enrolled in MITx: 6.871x, Machine Learning for Healthcare☆20Updated 4 years ago
- Reusable BatchBALD implementation☆79Updated last year
- Resources for Machine Learning Explainability☆86Updated last year
- Large-scale uncertainty benchmark in deep learning.☆65Updated 6 months ago
- AutoML Two-Sample Test☆19Updated 3 years ago
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆43Updated 3 years ago
- Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.☆18Updated last year
- Combating hidden stratification with GEORGE☆64Updated 4 years ago
- Updated code base for GlanceNets: Interpretable, Leak-proof Concept-based models☆25Updated 2 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated 2 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆44Updated 5 months ago
- Efficient Computation and Analysis of Distributional Shapley Values (AISTATS 2021)☆22Updated 2 years ago
- Unsupervised visualization of image datasets using contrastive learning☆116Updated 6 months ago
- A repo for transfer learning with deep tabular models☆104Updated 2 years ago
- This is the code for the paper Jacobian-based Causal Discovery with Nonlinear ICA, demonstrating how identifiable representations (partic…☆20Updated last year
- For calculating Shapley values via linear regression.☆71Updated 4 years ago
- Codebase for "Demystifying Black-box Models with Symbolic Metamodels", NeurIPS 2019.☆52Updated 6 years ago