6 papers
Learning-Guided Integration Contours Construction for Fast Large-Scale Generalized Eigensolvers
Yeqiu Chen, Ziyan Liu, Hong Wang +1
Solving large-scale Generalized Eigenvalue Problems (GEPs) is a fundamental yet computationally prohibitive task in science and engineering. As a promising direction, contour integ…
Learning Neural Operators from Partial Observations via Latent Autoregressive Modeling
Jingren Hou, Hong Wang, Pengyu Xu +3
Real-world scientific applications frequently encounter incomplete observational data due to sensor limitations, geographic constraints, or measurement costs. Although neural opera…
HGATSolver: A Heterogeneous Graph Attention Solver for Fluid-Structure Interaction
Qin-Yi Zhang, Hong Wang, Siyao Liu +6
Fluid-structure interaction (FSI) systems involve distinct physical domains, fluid and solid, governed by different partial differential equations and coupled at a dynamic interfac…
Accelerating IC Thermal Simulation Data Generation via Block Krylov and Operator Action
Hong Wang, Wenkai Yang, Jie Wang +6
Recent advances in data-driven approaches, such as neural operators (NOs), have shown substantial efficacy in reducing the solution time for integrated circuit (IC) thermal simulat…
Self-Attention to Operator Learning-based 3D-IC Thermal Simulation
Zhen Huang, Hong Wang, Wenkai Yang +6
Thermal management in 3D ICs is increasingly challenging due to higher power densities. Traditional PDE-solving-based methods, while accurate, are too slow for iterative design. Ma…
Unveiling the critical factors in crystal structure graph representation: a comparative analysis using streamlined MLPSets frameworks
Hongwei Du, Hong Wang
Graph Neural Networks have rapidly advanced in materials science and chemistry,with their performance critically dependent on comprehensive representations of crystal or molecular…