[ICML'24W] Revisiting Random Walks for Learning on Graphs, in PyTorch
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Updated
Jul 3, 2024
[ICML'24W] Revisiting Random Walks for Learning on Graphs, in PyTorch
Basic Invariant Test Practice in Foundry
DELA - Disentanglement Learning Archive
Code for "Environment Diversification with Multi-head Neural Network for Invariant Learning" (NeurIPS 2022)
[NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?
[NeurIPS 2023] Understanding and Improving Feature Learning for Out-of-Distribution Generalization
Causal Disentangled Recommendation Against Preference Shifts (TOIS), 2023
Ratioanle-aware Graph Contrastive Learning codebase
This repo contains code for Invariant Grounding for Video Question Answering
Tools for exploiting Morphological Symmetries in robotics
[KDD'2023] "KGRec: Knowledge Graph Self-Supervised Rationalization for Recommendation"
[ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization
[NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs
Official code of "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)
GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]
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