Jun 4, 2024 · To address long-range dependencies, we introduce Continuous-Time Graph Anti-Symmetric Network (CTAN). Grounded within the ordinary differential ...
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Jun 4, 2024 · In this paper, we propose the continuous-time graph anti-symmetric network (CTAN), a framework for learning of C-TDGs with scalable long range ...
Jul 29, 2024 · To address long-range dependencies, we introduce Continuous-Time Graph Anti-Symmetric Network (CTAN). Grounded within the ordinary differential ...
Official reference implementation of our paper "Long Range Propagation on Continuous-Time Dynamic Graphs" accepted at ICML24 and "Effective Non-Dissipative ...
Nov 26, 2023 · This paper presents a deep graph network called CTAN on continuous-time dynamic graphs. The CTAN model is designed within the ordinary differential equations ...
Duration: 38:31
Posted: Nov 3, 2024
Posted: Nov 3, 2024
Jun 5, 2024 · This paper introduces the Long-Range Dynamic Graph Neural Network (LR-DGNN), a novel approach to modeling long-range dependencies in continuous-time dynamic ...
In this work, we present Continuous-Time Graph Anti-Symmetric Network (CTAN), a DGN for C-TDGs designed within the ordinary differential equations framework ...
Specifically, we introduce a novel method for encoding continuous-time dynamic graphs, modeling the propagation process through two dynamic graphs: a temporal ...
Awesome papers (codes) about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs) and their applications.