kakaobrain / irm-empirical-studyLinks
An Empirical Study of Invariant Risk Minimization
☆27Updated 5 years ago
Alternatives and similar repositories for irm-empirical-study
Users that are interested in irm-empirical-study are comparing it to the libraries listed below
Sorting:
- ☆63Updated 5 years ago
- ☆65Updated last year
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆43Updated 4 years ago
- ☆31Updated 4 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
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆91Updated 5 years ago
- ☆26Updated 5 years ago
- Code for the NIPS 2018 paper "Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions"☆18Updated 4 years ago
- ☆34Updated 4 years ago
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 3 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 3 years ago
- ☆32Updated 7 years ago
- ☆37Updated 2 years ago
- Code for "Neural causal learning from unknown interventions"☆104Updated 5 years ago
- Code for Environment Inference for Invariant Learning (ICML 2021 Paper)☆51Updated 4 years ago
- "Predict, then Interpolate: A Simple Algorithm to Learn Stable Classifiers" ICML 2021☆18Updated 4 years ago
- Robust Learning with the Hilbert-Schmidt Independence Criterion☆49Updated 5 years ago
- ☆21Updated 5 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 4 years ago
- Code accompanying paper: Meta-Learning to Improve Pre-Training☆37Updated 4 years ago
- Active and Sample-Efficient Model Evaluation☆26Updated 7 months ago
- ☆45Updated 3 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆43Updated 2 years ago
- ☆32Updated 3 years ago
- ☆33Updated 4 years ago
- Improving Transformation Invariance in Contrastive Representation Learning☆13Updated 4 years ago
- Tensorflow implementation of "Meta Dropout: Learning to Perturb Latent Features for Generalization" (ICLR 2020)☆27Updated 5 years ago
- ☆12Updated 6 years ago
- Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…☆63Updated 5 years ago
- Domain Adaptation as a Problem of Inference on Graphical Models☆29Updated 5 years ago