Tianqi-py / MLGNCLinks
Multi-label Node Classification
☆14Updated last year
Alternatives and similar repositories for MLGNC
Users that are interested in MLGNC are comparing it to the libraries listed below
Sorting:
- [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…☆62Updated 3 years ago
- [WWW 2023] "Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum" by Yuan Gao, Xiang Wang, Xiangnan He, Zhe…☆39Updated 2 years ago
- [NeurIPS 2022] The official PyTorch implementation of "Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dyna…☆54Updated 3 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
- [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders☆91Updated last year
- A collection of papers on Graph Structural Learning (GSL)☆57Updated last year
- [WSDM 2024] GAD-NR : Graph Anomaly Detection via Neighborhood Reconstruction☆52Updated last year
- Official code implementation for WSDM 23 paper Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs.☆34Updated 2 years ago
- [CIKM 2021] A PyTorch implementation of "ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning".☆49Updated 4 years ago
- [WWW'22] Towards Unsupervised Deep Graph Structure Learning☆143Updated 3 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆47Updated 3 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…☆87Updated last year
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated 2 years ago
- A curated list of publications and code about data augmentaion for graphs.☆63Updated 3 years ago
- Offical pytorch implementation of proposed NRGNN and Compared Methods in "NRGNN: Learning a Label Noise-Resistant Graph Neural Network on…☆46Updated 3 years ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆59Updated 4 years ago
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆81Updated 3 years ago
- [ICML 2022] Local Augmentation for Graph Neural Networks☆66Updated last year
- Implementation of AAAI22 paper: MS-HGAT: Memory-enhanced Sequential Hypergraph Attention Network for Information Diffusion Prediction☆43Updated 2 years ago
- ☆38Updated 2 years ago
- Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".☆34Updated 2 years ago
- (ICLR 2022) Discovering Invariant Rationales for Graph Neural Networks☆132Updated 2 years ago
- [ICML'24] BAT: 🚀 Boost Class-imbalanced Node Classification with <10 lines of Code | 从拓扑视角出发10行代码改 善类别不平衡节点分类☆26Updated last year
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆43Updated 2 years ago
- ☆61Updated 3 years ago
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆53Updated 3 years ago
- ☆50Updated last year
- Source code for WWW 2021 paper "Lorentzian Graph Convolutional Networks"☆14Updated 4 years ago
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆34Updated last year