[NeurIPS 2023] “SODA: Robust Training of Test-Time Data Adaptors”
-
Updated
Oct 13, 2023 - Python
[NeurIPS 2023] “SODA: Robust Training of Test-Time Data Adaptors”
GradCAM-based Copy and Paste Augmentation
Code for the research paper Meta-learning with hierarchical models based on similarity of causal mechanisms
Multi-Domain Balanced Sampling Improves Out-of-Distribution Generalization of Chest X-ray Pathology Prediction Models
This work is a analysis of representations acquired for standard, OOD and Biased data on numerous objective functions.
Implementation codes for NeurIPS23 paper "Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts"
The Pytorch implementation for "Are Data-driven Explanations Robust against Out-of-distribution Data?" (CVPR 2023)
Code to reproduce the case studies of the 2024 paper "The Causal Chambers: Real Physical Systems as a Testbed for AI Methodology" by Juan L. Gamella, Jonas Peters and Peter Bühlmann.
Velodrome combines semi-supervised learning and out-of-distribution generalization (domain generalization) for drug response prediction and pharmacogenomics
[NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?
The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS 2023)
Potential energy ranking for domain generalization (DG)
Official PyTorch implementation of the ICCV'23 paper “Anomaly Detection under Distribution Shift”
Codes and datasets for NeurIPS21 paper “Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach”
[NeurIPS 2023] Understanding and Improving Feature Learning for Out-of-Distribution Generalization
Codes and datasets for ICML21 paper "Towards open-world recommendation: An inductive model-based collaborative filtering approach"
The Pytorch implementation for "Topology-aware Robust Optimization for Out-of-Distribution Generalization" (ICLR 2023)
[NeurIPS 2022] The official repository of Expression Learning with Identity Matching for Facial Expression Recognition
Distilling Large Vision-Language Model with Out-of-Distribution Generalizability (ICCV 2023)
Add a description, image, and links to the out-of-distribution-generalization topic page so that developers can more easily learn about it.
To associate your repository with the out-of-distribution-generalization topic, visit your repo's landing page and select "manage topics."