GRAPE for Fast and Scalable Graph Processing and random walk-based Embedding

12 October 2021

Papers citing "GRAPE for Fast and Scalable Graph Processing and random walk-based Embedding"

4 / 4 papers shown

Title
PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings Mehdi Ali M. Berrendorf Charles Tapley Hoyt Laurent Vermue Sahand Sharifzadeh Volker Tresp Jens Lehmann 13 124 0 28 Jul 2020
Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks Minjie Wang Da Zheng Zihao Ye Quan Gan Mufei Li ... J. Zhao Haotong Zhang Alex Smola Jinyang Li Zheng-Wei Zhang AI4CE GNN 169 665 0 03 Sep 2019
Billion-scale Network Embedding with Iterative Random Projection Ziwei Zhang Peng Cui Haoyang Li Xiao Wang Wenwu Zhu 67 73 0 07 May 2018
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 218 29,632 0 16 Jan 2013