Code for AAAI2020 paper "Graph Transformer for Graph-to-Sequence Learning"
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Updated
Mar 17, 2020 - Python
Code for AAAI2020 paper "Graph Transformer for Graph-to-Sequence Learning"
Codebase for paper: "Improving GCN with Transformer layer in social-based items recommendation"
Implementation of Power Law Graph Transformer for Machine Translation and Representation Learning.
Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.
2021 AAAI Modular Graph Transformer Networks for Multi-Label Image Classification; Official GitHub: https://github.com/ReML-AI/MGTN
Official Code Repository for the paper "Accurate Learning of Graph Representations with Graph Multiset Pooling" (ICLR 2021)
Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022
Implementation of "Pre-training Graph Transformer with Multimodal Side Information for Recommendation"
Graph molecular learning to predict blood-brain-barrier penetration and CNS drug delivery.
This repository reproduces the results in the paper "How expressive are transformers in spectral domain for graphs?"(published in TMLR)
Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)
Implementation for the paper: Representation Learning on Knowledge Graphs for Node Importance Estimation
Code for our paper "Attending to Graph Transformers"
Official Pytorch code for Structure-Aware Transformer.
[ICLR 2023] One Transformer Can Understand Both 2D & 3D Molecular Data (official implementation)
Video Graph Transformer for Video Question Answering (ECCV'22)
KDD-23 Automated 3D Pre-Training for Molecular Property Prediction
Deep learning toolkit for Drug Design with Pareto-based Multi-Objective optimization in Polypharmacology
The official implementation for ICLR23 spotlight paper "DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion"
SignNet and BasisNet
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