flaviovdf / label-shift
☆29Updated 3 years ago
Related projects: ⓘ
- A simple algorithm to identify and correct for label shift.☆22Updated 6 years ago
- Active and Sample-Efficient Model Evaluation☆24Updated 3 years ago
- Label shift experiments☆15Updated 3 years ago
- Code repository for our paper "Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift": https://arxiv.org/abs/1810.119…☆101Updated 5 months ago
- An Empirical Study of Invariant Risk Minimization☆28Updated 4 years ago
- MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space☆40Updated 3 years ago
- ☆30Updated 6 years ago
- A lightweight implementation of removal-based explanations for ML models.☆56Updated 3 years ago
- Code for the paper "Rethinking Importance Weighting for Deep Learning under Distribution Shift".☆24Updated 3 years ago
- (ICML 2021) Mandoline: Model Evaluation under Distribution Shift☆30Updated 3 years ago
- Python package for evaluating model calibration in classification☆19Updated 4 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 2 years ago
- Using / reproducing DAC from the paper "Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees"☆25Updated 3 years ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆35Updated 4 months ago
- A benchmark for distribution shift in tabular data☆40Updated 3 months ago
- Repository for code release of paper "Robust Variational Autoencoders for Outlier Detection and Repair of Mixed-Type Data" (AISTATS 2020)☆49Updated 4 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated 11 months ago
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆29Updated 4 years ago
- An Empirical Framework for Domain Generalization In Clinical Settings☆27Updated 2 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆34Updated last year
- Code for the NIPS 2018 paper "Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions"☆18Updated 3 years ago
- Self-Explaining Neural Networks☆14Updated last year
- Code for Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding☆21Updated last year
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆79Updated 3 months ago
- ☆29Updated 5 years ago
- An amortized approach for calculating local Shapley value explanations☆86Updated 9 months ago
- Neural Additive Models (Google Research)☆67Updated 2 years ago
- Implementation of the paper "Shapley Explanation Networks"☆84Updated 3 years ago
- ☆33Updated 3 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆50Updated 2 years ago