DELA - Disentanglement Learning Archive

Code for "Environment Diversification with Multi-head Neural Network for Invariant Learning" (NeurIPS 2022)

This repository provides implementations for sparse graph separation, power graph experiments, and chemical property prediction.

Causal Disentangled Recommendation Against Preference Shifts (TOIS), 2023

[ICLR'25 Spotlight] Revisiting Random Walks for Learning on Graphs (RWNN), in PyTorch

[NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?

This repo contains code for Invariant Grounding for Video Question Answering

[NeurIPS 2023] Understanding and Improving Feature Learning for Out-of-Distribution Generalization

Ratioanle-aware Graph Contrastive Learning codebase

[KDD'2023] "KGRec: Knowledge Graph Self-Supervised Rationalization for Recommendation"

Tools for exploiting Morphological Symmetries in robotics

[NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs

(ICLR 2022) Discovering Invariant Rationales for Graph Neural Networks

GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]