JonathanCrabbe / Label-Free-XAILinks
This repository contains the implementation of Label-Free XAI, a new framework to adapt explanation methods to unsupervised models. For more details, please read our ICML 2022 paper: 'Label-Free Explainability for Unsupervised Models'.
☆23Updated 2 years ago
Alternatives and similar repositories for Label-Free-XAI
Users that are interested in Label-Free-XAI are comparing it to the libraries listed below
Sorting:
- Code for "Consistent Estimators for Learning to Defer to an Expert" (ICML 2020)☆13Updated 2 years ago
- Code for the paper "Model Agnostic Interpretability for Multiple Instance Learning".☆13Updated 3 years ago
- Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI☆55Updated 2 years ago
- Code to study the generalisability of benchmark models on non-stationary EHRs.☆15Updated 5 years ago
- Learning clinical-decision rules with interpretable models.☆20Updated last year
- An Empirical Framework for Domain Generalization In Clinical Settings☆31Updated 3 years ago
- Repository for our NeurIPS 2022 paper "Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off" and our NeurIPS 2023 paper…☆63Updated last month
- Resources for Machine Learning Explainability☆80Updated 10 months ago
- Supercharging Imbalanced Data Learning WithCausal Representation Transfer☆12Updated 3 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆41Updated 2 years ago
- Code for the ICLR 2022 paper "Attention-based interpretability with Concept Transformers"☆40Updated 2 months ago
- ☆17Updated last year
- ☆10Updated 3 years ago
- Code repository for the AAAI 2022 paper "Do Feature Attribution Methods Correctly Attribute Features?"☆20Updated 3 years ago
- Code and results accompanying our paper titled Mixture Proportion Estimation and PU Learning: A Modern Approach at Neurips 2021 (Spotligh…☆44Updated last year
- ☆25Updated last year
- Self-Explaining Neural Networks☆42Updated 5 years ago
- An updated version of eICU Benchmark with an updated problem definition on LoS and Decompensation tasks☆11Updated 3 years ago
- Distributional Shapley: A Distributional Framework for Data Valuation☆30Updated last year
- Implementation of Adversarial Debiasing in PyTorch to address Gender Bias☆31Updated 4 years ago
- Official implementation of ICLR 2020 paper Unsupervised Clustering using Pseudo-semi-supervised Learning☆47Updated 4 years ago
- Code for the ICLR 2021 Paper "In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness"☆13Updated 3 years ago
- Code for "Generative causal explanations of black-box classifiers"☆34Updated 4 years ago
- A simple algorithm to identify and correct for label shift.☆21Updated 7 years ago
- SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks☆13Updated 2 years ago
- This is a benchmark to evaluate machine learning local explanaitons quality generated from any explainer for text and image data☆29Updated 4 years ago
- A lightweight implementation of removal-based explanations for ML models.☆59Updated 3 years ago
- ☆16Updated 3 years ago
- Fast Axiomatic Attribution for Neural Networks (NeurIPS*2021)☆16Updated 2 years ago
- (ICML 2021) Mandoline: Model Evaluation under Distribution Shift☆30Updated 4 years ago