daniellevy / fast-dro
PyTorch implementation of efficient algorithms for DRO with CVaR and Chi-Square uncertainty sets
☆57Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for fast-dro
- Distributional and Outlier Robust Optimization (ICML 2021)☆27Updated 3 years ago
- Benchmark for bi-level optimization solvers☆36Updated 2 weeks ago
- ☆42Updated 6 years ago
- Minimax Optimization, Stackelberg Games, Generative Adversarial Networks☆18Updated 4 years ago
- Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.☆16Updated 2 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 2 years ago
- ☆31Updated last year
- Code for the papers "Modeling the Second Player in Distributionally Robust Optimization" and "Distributionally Robust Models with Paramet…☆27Updated 2 years ago
- Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)☆22Updated last year
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 3 years ago
- Certifying Some Distributional Robustness with Principled Adversarial Training (https://arxiv.org/abs/1710.10571)☆45Updated 6 years ago
- Tilted Empirical Risk Minimization (ICLR '21)☆59Updated 11 months ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 2 years ago
- Experiments with distributionally robust optimization (DRO) for deep neural networks☆31Updated 5 years ago
- ☆66Updated 5 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 3 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆40Updated last year
- Limitations of the Empirical Fisher Approximation☆45Updated 4 years ago
- Official implementation for Training Certifiably Robust Neural Networks with Efficient Local Lipschitz Bounds (NeurIPS, 2021).☆22Updated 2 years ago
- Low-variance and unbiased gradient for backpropagation through categorical random variables, with application in variational auto-encoder…☆17Updated 4 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- Example code for paper "Bilevel Optimization: Nonasymptotic Analysis and Faster Algorithms"☆43Updated 2 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 5 years ago
- ☆65Updated 4 years ago
- This repository contains implementations of the paper, Bayesian Model-Agnostic Meta-Learning.☆59Updated 5 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated last year
- Code for Global Convergence of Block Coordinate Descent in Deep Learning (ICML 2019)☆34Updated 5 years ago
- ☆19Updated 4 years ago