Alternatives and similar repositories for robustopt

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

• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆42Updated 3 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆86Updated 5 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated last year
• YingzhenLi / VRbound
  code release for the NIPS 2016 paper
  ☆28Updated 9 years ago
• daniellevy / fast-dro
  PyTorch implementation of efficient algorithms for DRO with CVaR and Chi-Square uncertainty sets
  ☆63Updated 3 years ago
• RuntianZ / doro
  Distributional and Outlier Robust Optimization (ICML 2021)
  ☆28Updated 4 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
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆101Updated 7 years ago
• mingzhang-yin / SIVI
  A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…
  ☆54Updated last year
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 6 years ago
• BB-UCL / Lasagne
  ☆13Updated 7 years ago
• facebookresearch / InvarianceUnitTests
  Toy datasets to evaluate algorithms for domain generalization and invariance learning.
  ☆43Updated 4 years ago
• SeojinBang / VIBI
  Explaining a black-box using Deep Variational Information Bottleneck Approach
  ☆46Updated 3 years ago
• dilinwang820 / adaptive-f-divergence
  A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"
  ☆20Updated 6 years ago
• JonathanWenger / pycalib
  Non-Parametric Calibration for Classification (AISTATS 2020)
  ☆19Updated 3 years ago
• AMLab-Amsterdam / MNF_VBNN
  Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks
  ☆66Updated 5 years ago
• pawni / BayesByHypernet
  Code for the paper Implicit Weight Uncertainty in Neural Networks
  ☆65Updated 6 years ago
• alexalemi / vib_demo
  ☆93Updated 3 years ago
• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆50Updated 7 years ago
• reiinakano / invariant-risk-minimization
  Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893
  ☆91Updated 5 years ago
• duchi-lab / certifiable-distributional-robustness
  Certifying Some Distributional Robustness with Principled Adversarial Training (https://arxiv.org/abs/1710.10571)
  ☆45Updated 7 years ago
• StanfordASL / moca
  ☆32Updated 3 years ago
• widedeepnetworks / widedeepnetworks
  Code for the paper Gaussian process behaviour in wide deep networks
  ☆46Updated 7 years ago
• kohpangwei / group-influence-release
  ☆50Updated 2 years ago
• YingzhenLi / vae_renyi_divergence
  A tensorflow implementation of VAE training with Renyi divergence
  ☆31Updated 9 years ago
• cambridge-mlg / SPVAE
  Tensorflow code for "Hierarchical Decompositional Mixtures of Variational Autoencoders" (ICML'19)
  ☆12Updated 5 years ago
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆67Updated 6 years ago
• otokonoko8 / implicit-variational-inference
  The collection of recent papers about variational inference
  ☆84Updated 6 years ago
• mauriziofilippone / deep_gp_random_features
  ☆40Updated 6 years ago
• ron-amit / meta-learning-adjusting-priors
  Implementation of the paper "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory", Ron Amit and Ron Meir, ICML 2018
  ☆22Updated 6 years ago