namkoong-lab / whyshift
A python package providing a benchmark with various specified distribution shift patterns.
☆56Updated 11 months ago
Related projects ⓘ
Alternatives and complementary repositories for whyshift
- The code for the paper 'Heterogeneous Risk Minimization' of ICML2021.☆24Updated 3 years ago
- Benchmark for Natural Temporal Distribution Shift (NeurIPS 2022)☆63Updated last year
- This is the implementation for the NeurIPS 2022 paper: ZIN: When and How to Learn Invariance Without Environment Partition?☆22Updated last year
- ☆23Updated last year
- This is the project for IRM methods☆12Updated 3 years ago
- Official repo for AAAI 2023 paper "Stable Learning via Sparse Variable Independence".☆12Updated 5 months ago
- Disentangled gEnerative cAusal Representation (DEAR)☆56Updated 2 years ago
- Code for Model Agnostic Sample Reweighting for Out-of-Distribution Learning☆43Updated last year
- The code for our NeurIPS 2021 paper "Kernelized Heterogeneous Risk Minimization".☆12Updated 3 years ago
- A package of distributionally robust optimization (DRO) methods. Implemented via cvxpy and PyTorch☆55Updated 2 weeks ago
- Official code of "Boosting Differentiable Causal Discovery via Adaptive Sample Reweighting" (2023 ICLR)☆16Updated last year
- LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.☆34Updated 2 years ago
- A curated list of papers and resources about the distribution shift in machine learning.☆104Updated last year
- ☆43Updated 2 years ago
- Experiments to reproduce results in Interventional Causal Representation Learning.☆25Updated last year
- A list of papers for group meeting☆15Updated 2 months ago
- Code for Environment Inference for Invariant Learning (ICML 2021 Paper)☆49Updated 3 years ago
- ☆12Updated last year
- This is the code for the paper Bayesian Invariant Risk Minmization of CVPR 2022.☆42Updated last year
- ☆48Updated 2 years ago
- Officially unofficial PyTorch code for the NIPS paper 'Natural-Parameter Networks: A Class of Probabilistic Neural Networks'☆11Updated 3 years ago
- Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution …☆73Updated 2 years ago
- ☆19Updated 3 years ago
- This is an Uncertainty Study Arxiv☆11Updated 3 weeks ago
- [ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization☆50Updated 7 months ago
- ☆15Updated 2 years ago
- Code for Estimating Multi-cause Treatment Effects via Single-cause Perturbation (NeurIPS 2021)☆12Updated 2 years ago
- Source code of "What Makes Graph Neural Networks Miscalibrated?" (NeurIPS 2022)☆21Updated last year
- VAEs and nonlinear ICA: a unifying framework☆43Updated 5 years ago
- On the Role of Sparsity and DAG Constraints for Learning Linear DAGs☆33Updated 3 years ago