Alternatives and similar repositories for invariant-risk-minimization

Users that are interested in invariant-risk-minimization are comparing it to the libraries listed below

• capybaralet / REx_code_release
  ☆63Updated 4 years ago
• salesforce / corr_based_prediction
  This repo provides code used in the paper "Predicting with High Correlation Features" (https://arxiv.org/abs/1910.00164):
  ☆54Updated last month
• ermongroup / smile-mi-estimator
  PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"
  ☆73Updated 5 years ago
• yaodongyu / Rethink-BiasVariance-Tradeoff
  Rethinking Bias-Variance Trade-off for Generalization of Neural Networks
  ☆49Updated 4 years ago
• hendrycks / pre-training
  Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
  ☆100Updated 3 years ago
• MadryLab / BREEDS-Benchmarks
  ☆55Updated 4 years ago
• soochan-lee / CN-DPM
  Official code for ICLR 2020 paper "A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning."
  ☆100Updated 4 years ago
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆42Updated last year
• bneyshabur / generalization-bounds
  Computing various measures and generalization bounds on convolutional and fully connected networks
  ☆35Updated 6 years ago
• kohpangwei / group-influence-release
  ☆50Updated 2 years ago
• ecreager / eiil
  Code for Environment Inference for Invariant Learning (ICML 2021 Paper)
  ☆50Updated 3 years ago
• facebookresearch / InvarianceUnitTests
  Toy datasets to evaluate algorithms for domain generalization and invariance learning.
  ☆42Updated 3 years ago
• anniesch / jtt
  Code for "Just Train Twice: Improving Group Robustness without Training Group Information"
  ☆71Updated last year
• YugeTen / fish
  Official implementation of paper Gradient Matching for Domain Generalization
  ☆122Updated 3 years ago
• harshays / simplicitybiaspitfalls
  The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)
  ☆40Updated last year
• IBM / OoD
  Repository for theory and methods for Out-of-Distribution (OoD) generalization
  ☆63Updated 3 years ago
• alexalemi / vib_demo
  ☆91Updated 3 years ago
• AlexMeinke / certified-certain-uncertainty
  A way to achieve uniform confidence far away from the training data.
  ☆38Updated 4 years ago
• conormdurkan / neural-statistician
  PyTorch Implementation of Neural Statistician
  ☆60Updated 3 years ago
• Angie-Liu / labelshift
  Regularized Learning under label shifts
  ☆18Updated 6 years ago
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆49Updated 3 years ago
• stanford-futuredata / sinkhorn-label-allocation
  Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in fu…
  ☆53Updated 3 years ago
• locuslab / projected_sinkhorn
  ☆87Updated 10 months ago
• ricvolpi / generalize-unseen-domains
  Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018
  ☆121Updated 5 years ago
• avirmaux / lipEstimation
  ☆58Updated 2 years ago
• bethgelab / InDomainGeneralizationBenchmark
  ☆34Updated 3 years ago
• dcmoyer / inv-rep
  Code for Invariant Rep. Without Adversaries (NIPS 2018)
  ☆35Updated 5 years ago
• mpezeshki / Gradient_Starvation
  Gradient Starvation: A Learning Proclivity in Neural Networks
  ☆61Updated 4 years ago
• fmu2 / gradfeat20
  Gradients as Features for Deep Representation Learning
  ☆43Updated 5 years ago
• p-lambda / gradual_domain_adaptation
  ☆37Updated 4 years ago