PIE: a Parameter and Inference Efficient Solution for Large Scale Knowledge Graph Embedding Reasoning

29 April 2022

Papers citing "PIE: a Parameter and Inference Efficient Solution for Large Scale Knowledge Graph Embedding Reasoning"

4 / 4 papers shown

Title
From Wide to Deep: Dimension Lifting Network for Parameter-efficient Knowledge Graph Embedding Borui Cai Yong Xiang Longxiang Gao Di Wu Heng Zhang Jiongdao Jin Tom H. Luan 42 1 0 22 Mar 2023
BESS: Balanced Entity Sampling and Sharing for Large-Scale Knowledge Graph Completion A. Cattaneo Daniel Justus Harry Mellor Douglas Orr Jérôme Maloberti Ziqiang Liu Thorin Farnsworth Andrew Fitzgibbon Bla.zej Banaszewski Carlo Luschi 35 4 0 22 Nov 2022
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 345 1,960 0 09 Jun 2018
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 266 3,258 0 24 Nov 2016