Alternatives and similar repositories for irm-empirical-study

Users that are interested in irm-empirical-study are comparing it to the libraries listed below

• capybaralet / REx_code_release
  ☆63Updated 5 years ago
• ahujak / IB-IRM
  ☆31Updated 4 years ago
• ec6dde01667145e58de60f864e05a4 / CausalOptimizationAnon
  ☆65Updated last year
• facebookresearch / InvarianceUnitTests
  Toy datasets to evaluate algorithms for domain generalization and invariance learning.
  ☆42Updated 4 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
• reiinakano / invariant-risk-minimization
  Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893
  ☆91Updated 5 years ago
• Faruk-Ahmed / predictive_group_invariance
  ☆34Updated 4 years ago
• IBM / OoD
  Repository for theory and methods for Out-of-Distribution (OoD) generalization
  ☆63Updated 3 years ago
• mgong2 / DA_Infer
  Domain Adaptation as a Problem of Inference on Graphical Models
  ☆29Updated 4 years ago
• caus-am / dom_adapt
  Code for the NIPS 2018 paper "Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions"
  ☆18Updated 4 years ago
• AMLab-Amsterdam / DataAugmentationInterventions
  ☆26Updated 5 years ago
• ecreager / eiil
  Code for Environment Inference for Invariant Learning (ICML 2021 Paper)
  ☆51Updated 4 years ago
• jlko / active-testing
  Active and Sample-Efficient Model Evaluation
  ☆26Updated 6 months ago
• SeojinBang / VIBI
  Explaining a black-box using Deep Variational Information Bottleneck Approach
  ☆46Updated 3 years ago
• kimjeyoung / SNGP-BERT-Pytorch
  This is reimplementation of "Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness" in Pyt…
  ☆52Updated 4 years ago
• mfederici / dsit
  Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"
  ☆25Updated 4 years ago
• bethgelab / InDomainGeneralizationBenchmark
  ☆33Updated 4 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 4 years ago
• mrojascarulla / causal_transfer_learning
  ☆32Updated 7 years ago
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆43Updated 2 years ago
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆27Updated 5 years ago
• aniruddhraghu / meta-pretraining
  Code accompanying paper: Meta-Learning to Improve Pre-Training
  ☆37Updated 4 years ago
• yixinwang / representation-causal-public
  ☆45Updated 3 years ago
• YujiaBao / Predict-then-Interpolate
  "Predict, then Interpolate: A Simple Algorithm to Learn Stable Classifiers" ICML 2021
  ☆18Updated 4 years ago
• danielgreenfeld3 / XIC
  Robust Learning with the Hilbert-Schmidt Independence Criterion
  ☆49Updated 5 years ago
• geifmany / uncertainty_ICLR
  Code for the paper "Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers" published in ICLR 2019
  ☆14Updated 6 years ago
• TongtongFANG / DIW
  Code for the paper "Rethinking Importance Weighting for Deep Learning under Distribution Shift".
  ☆30Updated 4 years ago
• haebeom-lee / metadrop
  Tensorflow implementation of "Meta Dropout: Learning to Perturb Latent Features for Generalization" (ICLR 2020)
  ☆27Updated 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
• tjoo512 / belief-matching-framework
  Belief matching framework official implementation
  ☆41Updated 2 years ago