yxzwang / PhenomNNLinks
Codes for Paper: From Hypergraph Energy Functions to Hypergraph Neural Networks
☆22Updated 2 years ago
Alternatives and similar repositories for PhenomNN
Users that are interested in PhenomNN are comparing it to the libraries listed below
Sorting:
- PyTorch implementation of GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks☆36Updated 2 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆48Updated 3 years ago
- ☆29Updated 3 years ago
- Graph Transformers for Large Graphs☆21Updated last year
- KDD23 - Classification of Edge-Dependent Labels of Nodes in Hypergraphs☆18Updated last year
- Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)☆54Updated 2 years ago
- The open source code for ICDM2022 paper "Unifying Graph Contrastive Learning with Flexible Contextual Scopes"☆21Updated 2 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆59Updated 2 years ago
- ☆14Updated 3 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- ☆16Updated last year
- ☆19Updated 3 years ago
- CIKM2022: source code for "hypergraph learning with line expansion" paper☆20Updated 2 years ago
- Pytorch implementation of WWW'23:"Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs"☆15Updated 2 years ago
- [ICLR 2024] VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs☆100Updated last year
- Official Repo of SimTeG☆42Updated last year
- GFT: Graph Foundation Model with Transferable Tree Vocabulary, NeurIPS 2024.☆47Updated last month
- CAT-Walk is an inducive method that learns hyperedge representations via a novel higher-order random walk, SetWalk.☆15Updated last year
- [ICLR 2023] MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization☆77Updated 2 years ago
- ☆13Updated 4 years ago
- The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".☆33Updated 3 years ago
- Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization (NeurIPS 21')☆23Updated 3 years ago
- [ICLR 2023] "Equivariant Hypergraph Diffusion Neural Operators" by Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li☆46Updated 11 months ago
- ☆15Updated 2 years ago
- The implementation of HyperND from the Nonlinear Feature Diffusion on Hypergraphs paper☆13Updated 3 years ago
- [VLDB'23] SUREL+ is a novel set-based computation framework for scalable subgraph-based graph representation learning.☆17Updated 3 months ago
- [NeurIPS 2022] The official PyTorch implementation of "Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dyna…☆54Updated 2 years ago
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆42Updated 2 years ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆81Updated 3 years ago
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", wh…☆88Updated last year