graphdeeplearning Goto Github PK
Name: Graph Deep Learning Lab
Type: Organization
Bio: We investigate fundamental techniques in Graph Deep Learning, a new framework that combines graph theory and deep neural networks.
Location: Singapore
Graph Deep Learning Lab's Projects
benchmarking-gnns
Repository for benchmarking graph neural networks
graph-convnet-tsp
Code for the paper 'An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem' (arXiv Pre-print)
graphdeeplearning.github.io
Deploy website (https://github.com/graphdeeplearning/website) to GitHub pages
graphtransformer
Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.
graphtsne
PyTorch Implementation of GraphTSNE, ICLR’19
learning-paradigms-for-tsp
Code for the paper 'On Learning Paradigms for the Travelling Salesman Problem' (NeurIPS 2019 Graph Representation Learning Workshop)
multigraph_transformer
Official code of the paper "Multi-Graph Transformer for Free-Hand Sketch Recognition"
spatial_graph_convnets
PyTorch implementation of residual gated graph ConvNets, ICLR’18
textcategorization
:zap: Using deep learning (MLP, CNN, Graph CNN) to classify text in TensorFlow.
website
NTU Graph Deep Learning Lab Website
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