PolinaKirichenko / deep_feature_reweightingLinks
☆107Updated last year
Alternatives and similar repositories for deep_feature_reweighting
Users that are interested in deep_feature_reweighting are comparing it to the libraries listed below
Sorting:
- Official implementation of paper Gradient Matching for Domain Generalization☆122Updated 3 years ago
- Code for "Just Train Twice: Improving Group Robustness without Training Group Information"☆72Updated last year
- ☆45Updated 2 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆42Updated last year
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆24Updated 3 years ago
- Code for the ICLR 2022 paper. Salient Imagenet: How to discover spurious features in deep learning?☆40Updated 2 years ago
- LISA for ICML 2022☆50Updated 2 years ago
- ☆40Updated 2 years ago
- Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization☆87Updated 3 years ago
- Learning from Failure: Training Debiased Classifier from Biased Classifier (NeurIPS 2020)☆91Updated 4 years ago
- The repository for the official Biased Action Recognition (BAR) dataset for the paper Learning from Failure: Training Debiased Classifier…☆33Updated 4 years ago
- Repo for the paper: "Agree to Disagree: Diversity through Disagreement for Better Transferability"☆36Updated 2 years ago
- [NeurIPS 2021] A Geometric Analysis of Neural Collapse with Unconstrained Features☆57Updated 2 years ago
- ☆55Updated 4 years ago
- ☆23Updated 3 years ago
- An Investigation of Why Overparameterization Exacerbates Spurious Correlations☆31Updated 5 years ago
- Benchmark for Natural Temporal Distribution Shift (NeurIPS 2022)☆67Updated 2 years ago
- MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts (ICLR 2022)☆109Updated 2 years ago
- ☆34Updated last month
- Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style☆52Updated 3 years ago
- On the Importance of Gradients for Detecting Distributional Shifts in the Wild☆56Updated 2 years ago
- ☆27Updated last year
- We propose a theoretically motivated method, Adversarial Training with informative Outlier Mining (ATOM), which improves the robustness o…☆57Updated 3 years ago
- A modern look at the relationship between sharpness and generalization [ICML 2023]☆43Updated last year
- ImageNet Testbed, associated with the paper "Measuring Robustness to Natural Distribution Shifts in Image Classification."☆119Updated last year
- ☆34Updated last year
- ☆36Updated 4 years ago
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆35Updated 3 years ago
- The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)☆41Updated last year
- Code for the paper "A Whac-A-Mole Dilemma Shortcuts Come in Multiples Where Mitigating One Amplifies Others"☆49Updated last year