Alternatives and similar repositories for wdro_local_perturbation

Users that are interested in wdro_local_perturbation are comparing it to the libraries listed below

• RuntianZ / doro
  Distributional and Outlier Robust Optimization (ICML 2021)
  ☆28Updated 4 years ago
• GiulsLu / Sinkhorn-Barycenters
  Sinkhorn Barycenters via Frank-Wolfe algorithm
  ☆27Updated 5 years ago
• dtak / ocbnn-public
  General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.
  ☆38Updated 3 years ago
• team-approx-bayes / kpriors
  Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.
  ☆16Updated 3 years ago
• daniellevy / fast-dro
  PyTorch implementation of efficient algorithms for DRO with CVaR and Chi-Square uncertainty sets
  ☆61Updated 3 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 5 years ago
• yaohungt / Pointwise_Dependency_Neural_Estimation
  ☆20Updated 5 years ago
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆51Updated 4 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆49Updated 5 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 3 years ago
• vivienseguy / Large-Scale-OT
  Stochastic algorithms for computing Regularized Optimal Transport
  ☆58Updated 7 years ago
• litian96 / TERM
  Tilted Empirical Risk Minimization (ICLR '21)
  ☆60Updated 2 years ago
• ykwon0407 / fast_dist_shapley
  Efficient Computation and Analysis of Distributional Shapley Values (AISTATS 2021)
  ☆22Updated 2 years ago
• namkoong-lab / robustopt
  ☆43Updated 7 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• iamalexkorotin / Wasserstein2Barycenters
  PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)
  ☆24Updated 3 years ago
• IBM / wasserstein-barycenters
  Code for our ICLR19 paper "Wasserstein Barycenters for Model Ensembling", Pierre Dognin, Igor Melnyk, Youssef Mroueh, Jarret Ross, Cicero…
  ☆22Updated 6 years ago
• tudor-berariu / fisher-information-matrix
  PyTorch implementation of FIM and empirical FIM
  ☆60Updated 7 years ago
• juho-lee / bnp
  Pytorch implementation of neural processes and variants
  ☆29Updated last year
• StanfordASL / moca
  ☆32Updated 3 years ago
• AnonymousNIPS2019 / DeepnetHessian
  The Full Spectrum of Deepnet Hessians at Scale: Dynamics with SGD Training and Sample Size
  ☆17Updated 6 years ago
• karlstratos / doe
  Difference-of-Entropies (DoE) Estimator
  ☆25Updated 3 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆27Updated 5 years ago
• francoispierrepaty / SubspaceRobustWasserstein
  Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"
  ☆29Updated 6 years ago
• gibipara92 / learning-explanations-hard-to-vary
  Code to implement the AND-mask and geometric mean to do gradient based optimization, from the paper "Learning explanations that are hard …
  ☆41Updated 5 years ago
• csinva / mdl-complexity
  MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".
  ☆18Updated 2 years ago
• lfochamon / csl
  csl: PyTorch-based Constrained Learning
  ☆12Updated 3 years ago
• jsikyoon / bmaml
  This repository contains implementations of the paper, Bayesian Model-Agnostic Meta-Learning.
  ☆61Updated 6 years ago
• kakaobrain / irm-empirical-study
  An Empirical Study of Invariant Risk Minimization
  ☆27Updated 5 years ago