reiinakano / invariant-risk-minimizationLinks
Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893
☆90Updated 5 years ago
Alternatives and similar repositories for invariant-risk-minimization
Users that are interested in invariant-risk-minimization are comparing it to the libraries listed below
Sorting:
- ☆63Updated 4 years ago
- This repo provides code used in the paper "Predicting with High Correlation Features" (https://arxiv.org/abs/1910.00164):☆54Updated 3 months ago
- ☆91Updated 3 years ago
- Official code for ICLR 2020 paper "A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning."☆100Updated 5 years ago
- PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"☆75Updated 5 years ago
- Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.☆176Updated last year
- PyTorch code to run synthetic experiments.☆424Updated 3 years ago
- ☆55Updated 5 years ago
- Rethinking Bias-Variance Trade-off for Generalization of Neural Networks☆49Updated 4 years ago
- ☆50Updated 2 years ago
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 3 years ago
- PyTorch Implementation of Neural Statistician☆60Updated 3 years ago
- A way to achieve uniform confidence far away from the training data.☆38Updated 4 years ago
- Code for "Just Train Twice: Improving Group Robustness without Training Group Information"☆72Updated last year
- Code for the paper "Understanding Generalization through Visualizations"☆61Updated 4 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆50Updated 4 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆42Updated last year
- ☆34Updated 3 years ago
- ☆124Updated last year
- Computing various measures and generalization bounds on convolutional and fully connected networks☆35Updated 6 years ago
- Implementation of the variational continual learning method☆193Updated 6 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 3 years ago
- Code for Invariant Rep. Without Adversaries (NIPS 2018)☆35Updated 5 years ago
- Hybrid Discriminative-Generative Training via Contrastive Learning☆75Updated 2 years ago
- The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)☆41Updated last year
- This repository contains implementations of the paper, Bayesian Model-Agnostic Meta-Learning.☆60Updated 6 years ago
- ☆34Updated 4 years ago
- A collection of Gradient-Based Meta-Learning Algorithms with pytorch☆63Updated 5 years ago
- Distributionally robust neural networks for group shifts☆276Updated 2 years ago
- Official implementation of paper Gradient Matching for Domain Generalization☆122Updated 3 years ago