DELA - Disentanglement Learning Archive

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

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

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

Causal Disentangled Recommendation Against Preference Shifts (TOIS), 2023

Ratioanle-aware Graph Contrastive Learning codebase

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

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

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"

[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]