Scalable Global Alignment Graph Kernel Using Random Features: From Node
Embedding to Graph Embedding

Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding

25 November 2019

Kun Xu

Charu C. Aggarwal

Papers citing "Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding"

8 / 8 papers shown

Title
Expectation-Complete Graph Representations with Homomorphisms Pascal Welke Maximilian Thiessen Fabian Jogl Thomas Gärtner 30 7 0 09 Jun 2023
Quasi-Monte Carlo Graph Random Features Isaac Reid K. Choromanski Adrian Weller 27 8 0 21 May 2023
Sublinear Time Approximation of Text Similarity Matrices Archan Ray Nicholas Monath Andrew McCallum Cameron Musco 32 7 0 17 Dec 2021
Distance-wise Prototypical Graph Neural Network in Node Imbalance Classification Yu-Chiang Frank Wang Siegfried Mercelis Tyler Derr 21 22 0 22 Oct 2021
Deep Graph Matching and Searching for Semantic Code Retrieval Xiang Ling Lingfei Wu Sai-gang Wang Gaoning Pan Tengfei Ma Fangli Xu A. Liu Chunming Wu S. Ji GNN 39 91 0 24 Oct 2020
Multilevel Graph Matching Networks for Deep Graph Similarity Learning Xiang Ling Lingfei Wu Sai-gang Wang Tengfei Ma Fangli Xu A. Liu Chunming Wu S. Ji 14 60 0 08 Jul 2020
Deep Multi-attributed Graph Translation with Node-Edge Co-evolution Xiaojie Guo Liang Zhao Cameron Nowzari S. Rafatirad Houman Homayoun Sai Manoj P D 45 27 0 22 Mar 2020
Graph Random Neural Features for Distance-Preserving Graph Representations Daniele Zambon Cesare Alippi L. Livi 21 1 0 09 Sep 2019