fannie1208 / CaNetLinks
[WWW2024 Oral] "Graph Out-of-Distribution Generalization via Causal Intervention”.
☆27Updated last year
Alternatives and similar repositories for CaNet
Users that are interested in CaNet are comparing it to the libraries listed below
Sorting:
- Code for AAAI-2024 paper: Graph Contrastive Invariant Learning from the Causal Perspective☆28Updated last year
- A collection of papers on Graph Structural Learning (GSL)☆56Updated last year
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆53Updated 2 years ago
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆43Updated 2 years ago
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 3 years ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆86Updated 11 months ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated 2 years ago
- The implementation for DropMessage.☆37Updated 2 years ago
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆56Updated 2 years ago
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆44Updated 2 years ago
- [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…☆97Updated 2 years ago
- An official PyTorch implementation of "Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels" (WSDM 2022))☆34Updated 3 years ago
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆37Updated 3 years ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆35Updated 2 years ago
- The source code of SpCo☆34Updated 2 years ago
- [ICML 2022] Local Augmentation for Graph Neural Networks☆65Updated last year
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆45Updated 3 years ago
- ☆27Updated 3 years ago
- ☆59Updated last year
- [ICML 2023] Linkless Link Prediction via Relational Distillation☆24Updated 2 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆94Updated 2 years ago
- Official implementation of 'All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining' published i…☆42Updated last year
- Label-free Node Classification on Graphs with Large Language Models (LLMS)☆87Updated last year
- ☆49Updated 2 years ago
- Tail-GNN: Tail-Node Graph Neural Networks☆35Updated 4 years ago
- Papers about out-of-distribution generalization on graphs.☆167Updated 2 years ago
- Ratioanle-aware Graph Contrastive Learning codebase☆44Updated 2 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆105Updated last year
- [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…☆17Updated 2 years ago
- Awesome literature on imbalanced learning on graphs☆75Updated last year