BorgwardtLab / SATLinks
Official Pytorch code for Structure-Aware Transformer.
☆258Updated 2 years ago
Alternatives and similar repositories for SAT
Users that are interested in SAT are comparing it to the libraries listed below
Sorting:
- Representing Long-Range Context for Graph Neural Networks with Global Attention☆131Updated 3 years ago
- The official implementation of NeurIPS22 spotlight paper "NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classifica…☆310Updated last year
- Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022☆260Updated 3 years ago
- Official Implementation of ICML 2023 paper: "A Generalization of ViT/MLP-Mixer to Graphs"☆160Updated last year
- A graph transformer framework☆77Updated 3 years ago
- A curated list of papers on pre-training for graph neural networks (Pre-train4GNN).☆198Updated 6 months ago
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆127Updated last year
- Subgraph Neural Networks (NeurIPS 2020)☆200Updated 4 years ago
- Source code for From Stars to Subgraphs (ICLR 2022)☆70Updated last year
- This is an official implementation for "GRIT: Graph Inductive Biases in Transformers without Message Passing".☆126Updated 7 months ago
- IJCAI‘23 Survey Track: Papers on Graph Pooling (GNN-Pooling)☆116Updated 3 months ago
- GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner in WWW'23☆164Updated 2 years ago
- [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders☆88Updated 8 months ago
- [ICML 2022] Local Augmentation for Graph Neural Networks☆66Updated last year
- Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)☆343Updated 3 years ago
- [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…☆113Updated 10 months ago
- [GRL+ @ ICML 2020] PyTorch implementation for "Deep Graph Contrastive Representation Learning" (https://arxiv.org/abs/2006.04131v2)☆329Updated last year
- Source code for how powerful are K-hop message passing graph neural networks (Neurips 2022)☆64Updated last year
- ☆156Updated 3 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆103Updated 3 weeks ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆169Updated last year
- Edge-Augmented Graph Transformer☆77Updated last year
- AAAI'21: Data Augmentation for Graph Neural Networks☆193Updated last year
- ☆135Updated 2 years ago
- Long Range Graph Benchmark, NeurIPS 2022 Track on D&B☆157Updated last year
- Implementation of Self-supervised Graph-level Representation Learning with Local and Global Structure (ICML 2021).☆80Updated 4 years ago
- Schedule for learning on graphs seminar☆109Updated last year
- Transformer-based Spectral Graph Neural Networks☆86Updated 9 months ago
- NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"☆52Updated last year
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆80Updated 3 years ago