BUPT-GAMMA / IGM
source code of AAAI 2024 paper "Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution Generalization".
☆16Updated 11 months ago
Alternatives and similar repositories for IGM:
Users that are interested in IGM are comparing it to the libraries listed below
- Code for AAAI-2024 paper: Graph Contrastive Invariant Learning from the Causal Perspective☆24Updated last year
- "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23☆30Updated last year
- [NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?☆21Updated 7 months ago
- Code for Revar, NeurIPS 2023 https://arxiv.org/abs/2310.18765☆12Updated last week
- This paper studies the problem of cross-network node classification to overcome the insufficiency of labeled data in a single network. It…☆25Updated 3 years ago
- StableGNN-Generalizing Graph Neural Networks on Out-Of-Distribution Graphs☆22Updated last year
- [WWW2024 Oral paper] "Graph Out-of-Distribution Generalization via Causal Intervention”.☆25Updated 5 months ago
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated last year
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆39Updated 2 years ago
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆31Updated 10 months ago
- [ICML 2022] Local Augmentation for Graph Neural Networks☆66Updated 10 months ago
- The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS…☆19Updated 5 months ago
- The official source code for "LTE4G: Long-Tail Experts for Graph Neural Networks" paper, accepted at CIKM 2022.☆39Updated 2 years ago
- ☆52Updated 2 years ago
- The code of “Prototypical Graph Contrastive Learning”. [TNNLS 2022]☆24Updated 2 years ago
- Code for ICML 2023 paper "Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs"☆17Updated last year
- Directional diffusion models☆36Updated 5 months ago
- Implementation of GCKM in our paper: Graph Convolutional Kernel Machine versus Graph Convolutional Networks, NeurIPS 2023.☆11Updated 11 months ago
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆43Updated last year
- [IJCAI'23] LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity☆17Updated 5 months ago
- Neighbor Contrastive Learning on Learnable Graph Augmentation☆36Updated 9 months ago
- PyTorch implementation of "PolyGCL: GRAPH CONTRASTIVE LEARNING via Learnable Spectral Polynomial Filters"☆12Updated last year
- NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure☆41Updated last year
- Ratioanle-aware Graph Contrastive Learning codebase☆41Updated last year
- The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"☆81Updated last year
- A collection of papers on Graph Structural Learning (GSL)☆54Updated last year
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 2 years ago
- [WWW 2022] "A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆16Updated 3 years ago
- The Open Source Code For ICML 2023 Paper "Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-pron…☆15Updated last year
- Code for IJCAI'24 paper: Where to Mask: Structure-Guided Masking for Graph Masked Autoencoders☆10Updated 11 months ago