jlko / active-testingLinks
Active and Sample-Efficient Model Evaluation
☆24Updated 2 weeks ago
Alternatives and similar repositories for active-testing
Users that are interested in active-testing are comparing it to the libraries listed below
Sorting:
- An Empirical Study of Invariant Risk Minimization☆27Updated 4 years ago
- Model Patching: Closing the Subgroup Performance Gap with Data Augmentation☆42Updated 4 years ago
- Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction☆36Updated 3 years ago
- Improving Transformation Invariance in Contrastive Representation Learning☆13Updated 4 years ago
- ☆45Updated 2 years ago
- ModelDiff: A Framework for Comparing Learning Algorithms☆56Updated last year
- MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space☆41Updated 4 years ago
- ☆35Updated last year
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- ☆35Updated 4 years ago
- (ICML 2021) Mandoline: Model Evaluation under Distribution Shift☆31Updated 3 years ago
- Combating hidden stratification with GEORGE☆63Updated 4 years ago
- DiWA: Diverse Weight Averaging for Out-of-Distribution Generalization☆31Updated 2 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆42Updated last year
- ☆34Updated 4 years ago
- ☆18Updated 3 years ago
- Code to implement the AND-mask and geometric mean to do gradient based optimization, from the paper "Learning explanations that are hard …☆39Updated 4 years ago
- Fine-grained ImageNet annotations☆29Updated 5 years ago
- ☆30Updated 3 years ago
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆24Updated 3 years ago
- Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning (AISTATS 2022 Oral)☆41Updated 2 years ago
- Code and results accompanying our paper titled RLSbench: Domain Adaptation under Relaxed Label Shift☆34Updated last year
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 4 years ago
- Pytorch code for "Improving Self-Supervised Learning by Characterizing Idealized Representations"☆41Updated 2 years ago
- ☆63Updated 4 years ago
- [NeurIPS 2020] Coresets for Robust Training of Neural Networks against Noisy Labels☆34Updated 4 years ago
- Implementation of the paper "Understanding anomaly detection with deep invertible networks through hierarchies of distributions and featu…☆41Updated 4 years ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆35Updated last year
- Code for "SAM as an Optimal Relaxation of Bayes", ICLR 2023.☆25Updated last year
- Do input gradients highlight discriminative features? [NeurIPS 2021] (https://arxiv.org/abs/2102.12781)☆13Updated 2 years ago