Hyperparameter-free and Explainable Whole Graph Embedding

Hyperparameter-free and Explainable Whole Graph Embedding

4 August 2021

Papers citing "Hyperparameter-free and Explainable Whole Graph Embedding"

11 / 11 papers shown

Title
TUDataset: A collection of benchmark datasets for learning with graphs Christopher Morris Nils M. Kriege Franka Bause Kristian Kersting Petra Mutzel Marion Neumann 233 820 0 16 Jul 2020
A Survey on Graph Kernels Nils M. Kriege Fredrik D. Johansson Christopher Morris 133 418 0 28 Mar 2019
Deep Network Embedding for Graph Representation Learning in Signed Networks X. Shen F. Chung GNN 46 89 0 07 Jan 2019
Learning Graph Embedding with Adversarial Training Methods Shirui Pan Ruiqi Hu S. Fung Guodong Long Jing Jiang Chengqi Zhang GNN GAN 57 285 0 04 Jan 2019
Network Representation Learning: A Survey Daokun Zhang Jie Yin Xingquan Zhu Chengqi Zhang GNN AI4TS 82 622 0 04 Dec 2017
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 476 20,138 0 30 Oct 2017
graph2vec: Learning Distributed Representations of Graphs A. Narayanan Mahinthan Chandramohan R. Venkatesan Lihui Chen Yang Liu Shantanu Jaiswal GNN 71 742 0 17 Jul 2017
node2vec: Scalable Feature Learning for Networks Aditya Grover J. Leskovec 186 10,873 0 03 Jul 2016
DeepWalk: Online Learning of Social Representations Bryan Perozzi Rami Al-Rfou Steven Skiena HAI 254 9,789 0 26 Mar 2014
Distributed Representations of Words and Phrases and their Compositionality Tomas Mikolov Ilya Sutskever Kai Chen G. Corrado J. Dean NAI OCL 394 33,521 0 16 Oct 2013
Efficient Estimation of Word Representations in Vector Space Tomas Mikolov Kai Chen G. Corrado J. Dean 3DV 668 31,489 0 16 Jan 2013

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