fel-thomas / Sobol-Attribution-MethodLinks
π Code for the paper: "Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis" (NeurIPS 2021)
β30Updated 2 years ago
Alternatives and similar repositories for Sobol-Attribution-Method
Users that are interested in Sobol-Attribution-Method are comparing it to the libraries listed below
Sorting:
- Explores the ideas presented in Deep Ensembles: A Loss Landscape Perspective (https://arxiv.org/abs/1912.02757) by Stanislav Fort, Huiyi β¦β65Updated 4 years ago
- Model-agnostic posthoc calibration without distributional assumptionsβ42Updated last year
- Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Controlβ67Updated 8 months ago
- Build and train Lipschitz constrained networks: TensorFlow implementation of k-Lipschitz layersβ96Updated 4 months ago
- Training and evaluating NBM and SPAM for interpretable machine learning.β78Updated 2 years ago
- Official codebase for "Distribution-Free, Risk-Controlling Prediction Sets"β85Updated last year
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.β38Updated 3 years ago
- Last-layer Laplace approximation code examplesβ82Updated 3 years ago
- Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".β36Updated 3 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorchβ88Updated last year
- β36Updated last year
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"β160Updated last year
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotligβ¦β150Updated 2 years ago
- This repository contains a Jax implementation of conformal training corresponding to the ICLR'22 paper "learning optimal conformal classiβ¦β130Updated 2 years ago
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true claβ¦β242Updated 2 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"β25Updated 3 years ago
- A repo for transfer learning with deep tabular modelsβ104Updated 2 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"β33Updated 2 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".β112Updated 3 years ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"β35Updated last year
- Conformal prediction for controlling monotonic risk functions. Simple accompanying PyTorch code for conformal risk control in computer viβ¦β67Updated 2 years ago
- Reusable BatchBALD implementationβ79Updated last year
- β109Updated 2 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831β36Updated 2 years ago
- Neural Additive Models (Google Research)β71Updated 3 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)β41Updated 2 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)β77Updated 3 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)β76Updated last year
- Wrap around any model to output differentially private prediction sets with finite sample validity on any dataset.β18Updated last year
- Official PyTorch implementation of "Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error"β36Updated last year