weitianxin / awesome-distribution-shift
A curated list of papers and resources about the distribution shift in machine learning.
☆112Updated last year
Alternatives and similar repositories for awesome-distribution-shift:
Users that are interested in awesome-distribution-shift are comparing it to the libraries listed below
- Benchmark for Natural Temporal Distribution Shift (NeurIPS 2022)☆65Updated 2 years ago
- Awesome coreset/core-set/subset/sample selection works.☆173Updated 9 months ago
- A python package providing a benchmark with various specified distribution shift patterns.☆57Updated last year
- FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods.☆28Updated 10 months ago
- This is the implementation for the NeurIPS 2022 paper: ZIN: When and How to Learn Invariance Without Environment Partition?☆22Updated 2 years ago
- Officially unofficial PyTorch code for the NIPS paper 'Natural-Parameter Networks: A Class of Probabilistic Neural Networks'☆11Updated 3 years ago
- [ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization☆53Updated 11 months ago
- Neural Tangent Kernel Papers☆108Updated 2 months ago
- [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift☆107Updated last year
- Official repository for CMU Machine Learning Department's 10732: Robustness and Adaptivity in Shifting Environments☆73Updated 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…☆92Updated last year
- GitHub Repo for ICLR 2023 Paper "Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks"☆60Updated last year
- The code for the paper 'Heterogeneous Risk Minimization' of ICML2021.☆24Updated 3 years ago
- A benchmark for distribution shift in tabular data☆51Updated 9 months ago
- VAEs and nonlinear ICA: a unifying framework☆47Updated 5 years ago
- Source code of "What Makes Graph Neural Networks Miscalibrated?" (NeurIPS 2022)☆22Updated last year
- A simple PyTorch implementation of influence functions.☆86Updated 9 months ago
- Code repository for the paper "Invariant and Transportable Representations for Anti-Causal Domain Shifts"☆16Updated 2 years ago
- Code for "Surgical Fine-Tuning Improves Adaptation to Distribution Shifts" published at ICLR 2023☆29Updated last year
- This is the code for the paper Bayesian Invariant Risk Minmization of CVPR 2022.☆44Updated last year
- Disentangled gEnerative cAusal Representation (DEAR)☆60Updated 2 years ago
- Code for Environment Inference for Invariant Learning (ICML 2021 Paper)☆50Updated 3 years ago
- Official PyTorch implementation of STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables (ICLR 2023 Spotlight)…☆55Updated 2 years ago
- Efficient Conditionally Invariant Representation Learning (ICLR 2023, Oral)☆21Updated 2 years ago
- Coresets via Bilevel Optimization☆65Updated 4 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
- Code for Transformed Distribution Matching (TDM) for Missing Value Imputation, ICML 2023☆12Updated last year
- [NeurIPS 2023] Understanding and Improving Feature Learning for Out-of-Distribution Generalization☆29Updated 9 months ago
- A Data-Centric library providing a unified interface for state-of-the-art methods for hardness characterisation of data points.☆24Updated 3 weeks ago
- Official code for the paper "Task2Vec: Task Embedding for Meta-Learning" (https://arxiv.org/abs/1902.03545, ICCV 2019)☆117Updated last year