oscarkey / explanations-by-minimizing-uncertainty
Code for "Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties"
☆18Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for explanations-by-minimizing-uncertainty
- Local explanations with uncertainty 💐!☆39Updated last year
- An Empirical Framework for Domain Generalization In Clinical Settings☆27Updated 2 years ago
- Self-Explaining Neural Networks☆13Updated last year
- [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift☆98Updated last year
- Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations is a ServiceNow Research project that was started at Elemen…☆13Updated last year
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆40Updated last year
- Code accompanying paper: Meta-Learning to Improve Pre-Training☆37Updated 3 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆74Updated 2 years ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆36Updated 6 months ago
- Code for "Generative causal explanations of black-box classifiers"☆33Updated 3 years ago
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 2 years ago
- Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI☆52Updated 2 years ago
- ☆65Updated 4 years ago
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆31Updated 3 years ago
- Official codebase for the paper "Provable concept learning for interpretable predictions using variational inference".☆13Updated 2 years ago
- Self-Explaining Neural Networks☆39Updated 4 years ago
- ☆22Updated 5 years ago
- A benchmark for distribution shift in tabular data☆43Updated 5 months ago
- Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.☆53Updated last year
- Code for "Just Train Twice: Improving Group Robustness without Training Group Information"☆66Updated 5 months ago
- Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style☆48Updated 2 years ago
- ☆34Updated 3 years ago
- ☆14Updated last year
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆38Updated 2 years ago
- Towards Robust Interpretability with Self-Explaining Neural Networks, Alvarez-Melis et al. 2018☆15Updated 5 years ago
- Learning Autoencoders with Relational Regularization☆44Updated 4 years ago
- Code for Environment Inference for Invariant Learning (ICML 2021 Paper)☆49Updated 3 years ago
- VAEs and nonlinear ICA: a unifying framework☆43Updated 5 years ago
- Disentangled gEnerative cAusal Representation (DEAR)☆56Updated 2 years ago
- Repository for our NeurIPS 2022 paper "Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off" and our NeurIPS 2023 paper…☆52Updated this week