ssagawa / overparam_spur_corrView external linksLinks
An Investigation of Why Overparameterization Exacerbates Spurious Correlations
☆30Jul 12, 2020Updated 5 years ago
Alternatives and similar repositories for overparam_spur_corr
Users that are interested in overparam_spur_corr are comparing it to the libraries listed below
Sorting:
- Code for "Just Train Twice: Improving Group Robustness without Training Group Information"☆73May 18, 2024Updated last year
- Post-processing for fair classification☆16Jun 30, 2025Updated 7 months ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆43Oct 24, 2023Updated 2 years ago
- ☆15Jan 30, 2021Updated 5 years ago
- Code for testing DCT plus Sparse (DCTpS) networks☆14Jun 15, 2021Updated 4 years ago
- Distributionally robust neural networks for group shifts☆294Jan 3, 2023Updated 3 years ago
- ☆12Oct 5, 2020Updated 5 years ago
- DiWA: Diverse Weight Averaging for Out-of-Distribution Generalization☆31Jan 31, 2023Updated 3 years ago
- Provably (and non-vacuously) bounding test error of deep neural networks under distribution shift with unlabeled test data.☆10Feb 27, 2024Updated last year
- Demonstrates failures of bias mitigation methods under varying types/levels of biases (WACV 2021)☆26Mar 31, 2024Updated last year
- A quick test of SIREN on out-of-sample tasks☆13Jul 4, 2020Updated 5 years ago
- [ICML 2023] "Robust Weight Signatures: Gaining Robustness as Easy as Patching Weights?" by Ruisi Cai, Zhenyu Zhang, Zhangyang Wang☆16May 4, 2023Updated 2 years ago
- Code implementing the experiments described in the NeurIPS 2018 paper "With Friends Like These, Who Needs Adversaries?".☆13Sep 11, 2020Updated 5 years ago
- Code for the ICLR 2021 Paper "In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness"☆13Oct 23, 2021Updated 4 years ago
- Code for Environment Inference for Invariant Learning (ICML 2021 Paper)☆51Jun 10, 2021Updated 4 years ago
- ☆12Jul 17, 2023Updated 2 years ago
- Code repo for the NeurIPS 2021 paper "Online Adaption to Label Distribution Shift".☆15Feb 15, 2023Updated 3 years ago
- Neural Network Genetic Algorithm library used for deep learning problems☆18Jun 2, 2021Updated 4 years ago
- ☆15Nov 6, 2022Updated 3 years ago
- ☆17Jun 20, 2024Updated last year
- [JMLR] TRADES + random smoothing for certifiable robustness☆14Sep 13, 2020Updated 5 years ago
- Code for the paper "Data Feedback Loops: Model-driven Amplification of Dataset Biases"☆18Sep 9, 2022Updated 3 years ago
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Jan 10, 2021Updated 5 years ago
- ☆34Aug 30, 2021Updated 4 years ago
- ☆34Nov 30, 2018Updated 7 years ago
- Self-Distillation with weighted ground-truth targets; ResNet and Kernel Ridge Regression☆19Oct 12, 2021Updated 4 years ago
- ☆14Jul 6, 2021Updated 4 years ago
- MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".☆18Jun 12, 2023Updated 2 years ago
- Predicting Out-of-Distribution Error with the Projection Norm☆19Jul 27, 2022Updated 3 years ago
- Group-conditional DRO to alleviate spurious correlations☆15Jul 15, 2021Updated 4 years ago
- ☆37Apr 16, 2021Updated 4 years ago
- The Python PSDD Package☆19Jul 20, 2025Updated 6 months ago
- Machine Learning Course Materials, Tsinghua IIIS☆19Aug 6, 2018Updated 7 years ago
- ☆38Jun 10, 2021Updated 4 years ago
- [ICML 2021] This is the official github repo for training L_inf dist nets with high certified accuracy.☆42Mar 16, 2022Updated 3 years ago
- Efficient empirical NTKs in PyTorch☆22Jun 13, 2022Updated 3 years ago
- Pytorch implementation of regularization methods for deep networks obtained via kernel methods.☆23Dec 27, 2019Updated 6 years ago
- Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)☆21Mar 24, 2023Updated 2 years ago
- ☆48Jan 17, 2023Updated 3 years ago