EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph Learning

22 March 2023

Papers citing "EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph Learning"

6 / 6 papers shown

Title
A Survey on Temporal Interaction Graph Representation Learning: Progress, Challenges, and Opportunities Pengfei Jiao Hongjiang Chen Xuan Guo Zhidong Zhao Dongxiao He Di Jin AI4CE 29 0 0 07 May 2025
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,412 0 11 Nov 2021
Position-enhanced and Time-aware Graph Convolutional Network for Sequential Recommendations Liwei Huang Yutao Ma Yanbo Liu Bohong Du Shuliang Wang Deyi Li GNN 16 52 0 12 Jul 2021
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 162 590 0 31 Dec 2020
Learning Sequence Encoders for Temporal Knowledge Graph Completion Alberto García-Durán Sebastijan Dumancic Mathias Niepert 187 395 0 10 Sep 2018
Scalable Link Prediction in Dynamic Networks via Non-Negative Matrix Factorization Linhong Zhu Dong Guo Junming Yin Greg Ver Steeg Aram Galstyan 43 199 0 13 Nov 2014