GradCAM-based Copy and Paste Augmentation
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Updated
Oct 10, 2022 - Python
GradCAM-based Copy and Paste Augmentation
Code for the research paper Meta-learning with hierarchical models based on similarity of causal mechanisms
[NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?
[NeurIPS 2023] “SODA: Robust Training of Test-Time Data Adaptors”
[NeurIPS 2023] Understanding and Improving Feature Learning for Out-of-Distribution Generalization
Implementation codes for NeurIPS23 paper "Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts"
The Pytorch implementation for "Topology-aware Robust Optimization for Out-of-Distribution Generalization" (ICLR 2023)
Potential energy ranking for domain generalization (DG)
Multi-Domain Balanced Sampling Improves Out-of-Distribution Generalization of Chest X-ray Pathology Prediction Models
The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS 2023)
The Pytorch implementation for "Are Data-driven Explanations Robust against Out-of-distribution Data?" (CVPR 2023)
Velodrome combines semi-supervised learning and out-of-distribution generalization (domain generalization) for drug response prediction and pharmacogenomics
[NeurIPS 2022] The official repository of Expression Learning with Identity Matching for Facial Expression Recognition
Official PyTorch implementation of the ICCV'23 paper “Anomaly Detection under Distribution Shift”
Distilling Large Vision-Language Model with Out-of-Distribution Generalizability (ICCV 2023)
The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"
Official implementation for the paper "Learning Substructure Invariance for Out-of-Distribution Molecular Representations" (NeurIPS 2022).
Code for ICML21 spotlight paper "Towards open-world recommendation: An inductive model-based collaborative filtering approach"
Mechanistically interpretable neurosymbolic AI (Nature Comput Sci 2024): losslessly compressing NNs to computer code and discovering new algorithms which generalize out-of-distribution and outperform human-designed algorithms
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