SeDyT: A General Framework for Multi-Step Event Forecasting via Sequence Modeling on Dynamic Entity Embeddings

9 September 2021

Papers citing "SeDyT: A General Framework for Multi-Step Event Forecasting via Sequence Modeling on Dynamic Entity Embeddings"

4 / 4 papers shown

Title
TASER: Temporal Adaptive Sampling for Fast and Accurate Dynamic Graph Representation Learning Gangda Deng Hongkuan Zhou Hanqing Zeng Yinglong Xia Christopher Leung Jianbo Li Rajgopal Kannan Viktor Prasanna 24 1 0 08 Feb 2024
Bending the Future: Autoregressive Modeling of Temporal Knowledge Graphs in Curvature-Variable Hyperbolic Spaces J. Sohn Mingyu Derek Ma Muhao Chen 27 2 0 12 Sep 2022
Model-Architecture Co-Design for High Performance Temporal GNN Inference on FPGA Hongkuan Zhou Bingyi Zhang R. Kannan Viktor Prasanna Carl E. Busart GNN 26 23 0 10 Mar 2022
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 267 1,945 0 09 Jun 2018