Alternatives and similar repositories for fast-dro:

Users that are interested in fast-dro are comparing it to the libraries listed below

• namkoong-lab / robustopt
  ☆42Updated 6 years ago
• benchopt / benchmark_bilevel
  Benchmark for bi-level optimization solvers
  ☆37Updated 3 weeks ago
• RuntianZ / doro
  Distributional and Outlier Robust Optimization (ICML 2021)
  ☆27Updated 3 years ago
• pmichel31415 / P-DRO
  Code for the papers "Modeling the Second Player in Distributionally Robust Optimization" and "Distributionally Robust Models with Paramet…
  ☆27Updated 2 years ago
• duchi-lab / certifiable-distributional-robustness
  Certifying Some Distributional Robustness with Principled Adversarial Training (https://arxiv.org/abs/1710.10571)
  ☆45Updated 6 years ago
• team-approx-bayes / kpriors
  Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.
  ☆16Updated 2 years ago
• prolearner / hypertorch
  ☆119Updated 6 months ago
• ykwon0407 / wdro_local_perturbation
  Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)
  ☆22Updated last year
• dtak / ocbnn-public
  General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
  ☆38Updated 2 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆81Updated 6 months ago
• JunjieYang97 / stocBiO
  Example code for paper "Bilevel Optimization: Nonasymptotic Analysis and Faster Algorithms"
  ☆43Updated 2 years ago
• team-approx-bayes / fromp
  Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"
  ☆44Updated 4 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆80Updated 4 years ago
• StanfordASL / moca
  ☆31Updated 2 years ago
• litian96 / TERM
  Tilted Empirical Risk Minimization (ICLR '21)
  ☆59Updated last year
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆30Updated 3 years ago
• activatedgeek / svgd
  PyTorch implementation of Stein Variational Gradient Descent
  ☆41Updated last year
• facebookresearch / InvarianceUnitTests
  Toy datasets to evaluate algorithms for domain generalization and invariance learning.
  ☆42Updated 3 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• IBM / OoD
  Repository for theory and methods for Out-of-Distribution (OoD) generalization
  ☆63Updated 2 years ago
• kilianFatras / variance_reduced_neural_networks
  Implementation of SVRG and SAGA optimization algorithms for deep learning topics.
  ☆70Updated 3 years ago
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆46Updated 4 years ago
• zixu1986 / Doubly_Stochastic_Gradients
  Code for doubly stochastic gradients
  ☆25Updated 10 years ago
• zalanborsos / bilevel_coresets
  Coresets via Bilevel Optimization
  ☆65Updated 4 years ago
• jsikyoon / bmaml
  This repository contains implementations of the paper, Bayesian Model-Agnostic Meta-Learning.
  ☆59Updated 5 years ago
• gd-zhang / Follow-the-Ridge
  Minimax Optimization, Stackelberg Games, Generative Adversarial Networks
  ☆18Updated 4 years ago
• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 3 years ago
• sungyubkim / GBML
  A collection of Gradient-Based Meta-Learning Algorithms with pytorch
  ☆63Updated 5 years ago