10 citations · 10 across the 4 of their papers we have counts for
4 papers
Hamiltonian Graph Inference Networks: Joint structure discovery and dynamics prediction for lattice Hamiltonian systems from trajectory data
Ru Geng, Panayotis Kevrekidis, Yixian Gao +2
Lattice Hamiltonian systems underpin models across condensed matter, nonlinear optics, and biophysics, yet learning their dynamics from data is obstructed by two unknowns: the inte…
Graph Attention Hamiltonian Neural Networks: A Lattice System Analysis Model Based on Structural Learning
Ru Geng, Yixian Gao, Jian Zu +1
A deep understanding of the intricate interactions between particles within a system is a key approach to revealing the essential characteristics of the system, whether it is an in…
-SGHN: A Robust Model for Learning Particle Interactions in Lattice Systems
Yixian Gao, Ru Geng, Panayotis Kevrekidis +2
We propose an -separable graph Hamiltonian network (-SGHN) that reveals complex interaction patterns between particles in lattice systems. Utilizing trajectory data, -SGHN…
Analysis of the Spatio-temporal Dynamics of COVID-19 in Massachusetts via Spectral Graph Wavelet Theory
Ru Geng, Yixian Gao, Hongkun Zhang +1
The rapid spread of COVID-19 disease has had a significant impact on the world. In this paper, we study COVID-19 data interpretation and visualization using open-data sources for 3…