TIDE: Time Derivative Diffusion for Deep Learning on Graphs

5 December 2022

Papers citing "TIDE: Time Derivative Diffusion for Deep Learning on Graphs"

9 / 9 papers shown

Title
COSMOS: Continuous Simplicial Neural Networks Aref Einizade Dorina Thanou Fragkiskos D. Malliaros Jhony H. Giraldo AI4CE 56 0 0 17 Mar 2025
Graph Fourier Neural Kernels (G-FuNK): Learning Solutions of Nonlinear Diffusive Parametric PDEs on Multiple Domains Shane E. Loeffler Zan Ahmad Syed Yusuf Ali Carolyna Yamamoto D. Popescu Alana Yee Yash Lal Natalia A. Trayanova Mauro Maggioni 31 2 0 06 Oct 2024
Synchronous Diffusion for Unsupervised Smooth Non-Rigid 3D Shape Matching Dongliang Cao Zorah Laehner Florian Bernard DiffM 35 0 0 11 Jul 2024
Spatiotemporal Forecasting Meets Efficiency: Causal Graph Process Neural Networks Aref Einizade Fragkiskos D. Malliaros Jhony H. Giraldo AI4TS 24 0 0 29 May 2024
Continuous Product Graph Neural Networks Aref Einizade Fragkiskos D. Malliaros Jhony H. Giraldo 14 1 0 29 May 2024
Graph Neural Aggregation-diffusion with Metastability Kaiyuan Cui Xinyan Wang Zicheng Zhang Weichen Zhao 23 2 0 29 Mar 2024
Smoothed Graph Contrastive Learning via Seamless Proximity Integration M. Behmanesh M. Ovsjanikov 16 0 0 23 Feb 2024
Understanding Oversmoothing in Diffusion-Based GNNs From the Perspective of Operator Semigroup Theory Weichen Zhao Chenguang Wang Xinyan Wang Congying Han Tiande Guo Tianshu Yu 38 0 0 23 Feb 2024
From Continuous Dynamics to Graph Neural Networks: Neural Diffusion and Beyond Andi Han Dai Shi Lequan Lin Junbin Gao AI4CE GNN 35 20 0 16 Oct 2023