Graph-COM / Neighborhood-Aware-Temporal-NetworkLinks
Yuhong Luo and Pan Li. Neighborhood-aware scalable temporal network representation learning. In Learning on Graphs, 2022.
☆27Updated 2 years ago
Alternatives and similar repositories for Neighborhood-Aware-Temporal-Network
Users that are interested in Neighborhood-Aware-Temporal-Network are comparing it to the libraries listed below
Sorting:
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆57Updated 2 years ago
- Graph Structured Neural Network☆40Updated 3 years ago
- ☆103Updated 2 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆106Updated 4 months ago
- Node Dependent Local Smoothing for Scalable Graph Learning (NeurIPS'21, Spotlight)☆22Updated 3 years ago
- ☆138Updated 2 years ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆86Updated 11 months ago
- ☆75Updated 3 years ago
- Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"☆39Updated 2 years ago
- Code of GAMLP for Open Graph Benchmark. KDD‘22☆63Updated 3 years ago
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆125Updated 3 years ago
- ☆29Updated 4 years ago
- How Powerful are Spectral Graph Neural Networks☆73Updated 2 years ago
- ☆22Updated 2 years ago
- This repo contains a reference implementation for the paper "Breaking the Limit of Graph Neural Networks by Improving the Assortativity o…☆32Updated 3 years ago
- Dynamic Graph Benchmark☆83Updated 2 years ago
- ☆19Updated 2 years ago
- [WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs☆116Updated 3 years ago
- This is the GitHub repository for our ICLR22 paper: "You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks"☆103Updated 2 years ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆170Updated last year
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆82Updated 2 years ago
- Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification☆81Updated 4 years ago
- NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"☆52Updated 2 years ago
- Code and dataset for paper "GRAND+: Scalable Graph Random Neural Networks"☆34Updated 3 years ago
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆120Updated 2 years ago
- PyTorch implementation of "Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited"☆41Updated 2 years ago
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆53Updated 2 years ago
- Pytorch implementation of EvenNet.☆20Updated 3 years ago
- Advances on machine learning of dynamic (temporal) graphs, covering the reading list of recent top academic conferences.☆61Updated 2 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆89Updated 4 years ago