HazyResearch / hidden-stratification
Combating hidden stratification with GEORGE
☆62Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for hidden-stratification
- Model Patching: Closing the Subgroup Performance Gap with Data Augmentation☆42Updated 4 years ago
- The official repository for "Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning" paper.☆40Updated 2 years ago
- Active and Sample-Efficient Model Evaluation☆24Updated 3 years ago
- Algorithms for abstention, calibration and domain adaptation to label shift.☆36Updated 4 years ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆155Updated 10 months ago
- Figures & code from the paper "Shortcut Learning in Deep Neural Networks" (Nature Machine Intelligence 2020)☆94Updated 2 years ago
- Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction☆35Updated 2 years ago
- Reusable BatchBALD implementation☆74Updated 8 months ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆40Updated last year
- ☆41Updated last year
- ☆34Updated 4 years ago
- Pytorch code for "Improving Self-Supervised Learning by Characterizing Idealized Representations"☆40Updated last year
- Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI☆52Updated 2 years ago
- Pytorch library for model calibration metrics and visualizations as well as recalibration methods. In progress!☆68Updated 6 months ago
- Estimating Example Difficulty using Variance of Gradients☆63Updated last year
- B-LRP is the repository for the paper How Much Can I Trust You? — Quantifying Uncertainties in Explaining Neural Networks☆18Updated 2 years ago
- Gradient Starvation: A Learning Proclivity in Neural Networks☆60Updated 3 years ago
- Fine-grained ImageNet annotations☆29Updated 4 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆40Updated 2 years ago
- An Empirical Framework for Domain Generalization In Clinical Settings☆28Updated 2 years ago
- ☆33Updated 3 years ago
- ☆34Updated 3 years ago
- Code accompanying paper: Meta-Learning to Improve Pre-Training☆37Updated 3 years ago
- ☆58Updated 2 years ago
- Original dataset release for CIFAR-10H☆82Updated 4 years ago
- Wasserstein Adversarial Active Learning☆29Updated 4 years ago
- ☆109Updated 2 years ago
- ☆65Updated 4 years ago
- An uncertainty-based random sampling algorithm for data augmentation☆30Updated 4 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated last year