ykwon0407 / wdro_local_perturbationLinks
Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)
☆21Updated 2 years ago
Alternatives and similar repositories for wdro_local_perturbation
Users that are interested in wdro_local_perturbation are comparing it to the libraries listed below
Sorting:
- Distributional and Outlier Robust Optimization (ICML 2021)☆28Updated 4 years ago
- Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.☆16Updated 3 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 5 years ago
- Sinkhorn Barycenters via Frank-Wolfe algorithm☆27Updated 5 years ago
- PyTorch implementation of efficient algorithms for DRO with CVaR and Chi-Square uncertainty sets☆63Updated 3 years ago
- ☆21Updated 5 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 3 years ago
- ☆43Updated 7 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆58Updated 7 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 3 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆43Updated 4 years ago
- ☆63Updated 5 years ago
- PyTorch implementation of the paper "Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization" (ICLR 2021)☆25Updated 3 years ago
- Learning Generative Models across Incomparable Spaces (ICML 2019)☆27Updated 5 years ago
- Code for our ICLR19 paper "Wasserstein Barycenters for Model Ensembling", Pierre Dognin, Igor Melnyk, Youssef Mroueh, Jarret Ross, Cicero…☆23Updated 6 years ago
- Pytorch implementation of neural processes and variants☆29Updated last year
- Source code for paper Conservative Uncertainty Estimation By Fitting Prior Networks (ICLR 2020)☆22Updated 3 years ago
- ☆32Updated 3 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 6 years ago
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 3 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆51Updated 4 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆78Updated 3 years ago
- PyTorch implementation of Stein Variational Gradient Descent☆47Updated 2 years ago
- ☆14Updated 2 years ago
- Variational Auto-Regressive Gaussian Processes for Continual Learning☆22Updated 4 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Efficient Computation and Analysis of Distributional Shapley Values (AISTATS 2021)☆22Updated 2 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- csl: PyTorch-based Constrained Learning☆12Updated 3 years ago
- 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