weitianxin / awesome-distribution-shiftLinks
A curated list of papers and resources about the distribution shift in machine learning.
☆123Updated 2 years ago
Alternatives and similar repositories for awesome-distribution-shift
Users that are interested in awesome-distribution-shift are comparing it to the libraries listed below
Sorting:
- Benchmark for Natural Temporal Distribution Shift (NeurIPS 2022)☆68Updated 2 years ago
- The repository contains lists of papers on causality and how relevant techniques are being used to further enhance deep learning era comp…☆99Updated 2 years ago
- Awesome coreset/core-set/subset/sample selection works.☆184Updated last year
- OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)☆99Updated 10 months ago
- A python package providing a benchmark with various specified distribution shift patterns.☆59Updated 2 years ago
- [ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization☆53Updated last year
- This is the implementation for the NeurIPS 2022 paper: ZIN: When and How to Learn Invariance Without Environment Partition?☆22Updated 3 years ago
- The code for the paper 'Heterogeneous Risk Minimization' of ICML2021.☆25Updated 4 years ago
- Data Optimization in Deep Learning: A Survey☆19Updated 2 years ago
- Official repository for CMU Machine Learning Department's 10732: Robustness and Adaptivity in Shifting Environments☆77Updated 3 years ago
- A benchmark for distribution shift in tabular data☆57Updated last year
- GitHub Repo for ICLR 2023 Paper "Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks"☆60Updated 2 years ago
- [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift☆111Updated 2 years ago
- Papers and online resources related to machine learning fairness☆75Updated 2 years ago
- This is the code for the paper Bayesian Invariant Risk Minmization of CVPR 2022.☆47Updated 2 years ago
- ☆37Updated 2 years ago
- Code for Environment Inference for Invariant Learning (ICML 2021 Paper)☆51Updated 4 years ago
- Code for coreset selection methods☆247Updated 2 years ago
- Neural Tangent Kernel Papers☆120Updated 11 months ago
- Optimal Transport Dataset Distance☆173Updated 3 years ago
- Official implementation for KDD'22 paper "Learning Fair Representation via Distributional Contrastive Disentanglement"☆23Updated 3 years ago
- 💱 A curated list of data valuation (DV) to design your next data marketplace☆135Updated 10 months ago
- Source code of "What Makes Graph Neural Networks Miscalibrated?" (NeurIPS 2022)☆24Updated 6 months ago
- Distributionally robust neural networks for group shifts☆290Updated 2 years ago
- [NeurIPS 2023] Understanding and Improving Feature Learning for Out-of-Distribution Generalization☆29Updated 7 months ago
- Code for "Surgical Fine-Tuning Improves Adaptation to Distribution Shifts" published at ICLR 2023☆29Updated 2 years ago
- Disentangled gEnerative cAusal Representation (DEAR)☆66Updated 3 years ago
- This is a curated list for Information Bottleneck Principle, in memory of Professor Naftali Tishby.☆382Updated last year
- Bayesian Low-Rank Adaptation of LLMs: BLoB [NeurIPS 2024] and TFB [NeurIPS 2025]☆31Updated 2 months ago
- ☆22Updated 6 years ago