CongWeilin / GraphMixerLinks
☆100Updated last year
Alternatives and similar repositories for GraphMixer
Users that are interested in GraphMixer are comparing it to the libraries listed below
Sorting:
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆83Updated 7 months ago
- Dynamic Graph Benchmark☆81Updated 2 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆103Updated last week
- Yuhong Luo and Pan Li. Neighborhood-aware scalable temporal network representation learning. In Learning on Graphs, 2022.☆27Updated 2 years ago
- ☆55Updated 3 years ago
- A collection of papers on Graph Structural Learning (GSL)☆54Updated last year
- Awesome Temporal Graph Learning is a collection of SOTA, novel temporal graph learning methods (papers, codes, and datasets).☆71Updated last month
- How Powerful are Spectral Graph Neural Networks☆72Updated last year
- Advances on machine learning of dynamic (temporal) graphs, covering the reading list of recent top academic conferences.☆61Updated last year
- A curated list of papers on graph structure learning (GSL).☆49Updated 5 months ago
- Official code implementation for WSDM 23 paper Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs.☆34Updated 2 years ago
- ☆135Updated last year
- Implementation Codes for NeurIPS22 paper "Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift"☆21Updated 2 years ago
- ☆57Updated 7 months ago
- [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…☆90Updated last year
- PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"☆54Updated 2 years ago
- Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification☆80Updated 4 years ago
- Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"☆38Updated 2 years ago
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆119Updated 2 years ago
- ☆36Updated 3 years ago
- An awesome collection of causality-inspired graph neural networks.☆79Updated 6 months ago
- ☆54Updated 9 months ago
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆123Updated 2 years ago
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆55Updated 2 years ago
- Paper list on GNNs + Differential Equations (ODE, PDE, SDE)☆27Updated 3 weeks ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆105Updated last year
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆89Updated 2 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆88Updated 3 years ago
- ☆76Updated 2 years ago
- TREND: TempoRal Event and Node Dynamics for Graph Representation Learning. WWW-2022.☆36Updated last year