64 citations · 87 across the 10 of their papers we have counts for
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Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling
Vivek Oommen, Aniruddha Bora, Zhen Zhang +1
We integrate neural operators with diffusion models to address the spectral limitations of neural operators in surrogate modeling of turbulent flows. While neural operators offer c…
SympGNNs: Symplectic Graph Neural Networks for identifiying high-dimensional Hamiltonian systems and node classification
Alan John Varghese, Zhen Zhang, George Em Karniadakis
Existing neural network models to learn Hamiltonian systems, such as SympNets, although accurate in low-dimensions, struggle to learn the correct dynamics for high-dimensional many…
CFDBench: A Large-Scale Benchmark for Machine Learning Methods in Fluid Dynamics
Yining Luo, Yingfa Chen, Zhen Zhang
In recent years, applying deep learning to solve physics problems has attracted much attention. Data-driven deep learning methods produce fast numerical operators that can learn ap…
Discovering a reaction-diffusion model for Alzheimer's disease by combining PINNs with symbolic regression
Zhen Zhang, Zongren Zou, Ellen Kuhl +1
Misfolded tau proteins play a critical role in the progression and pathology of Alzheimer's disease. Recent studies suggest that the spatio-temporal pattern of misfolded tau follow…
Learning Poisson systems and trajectories of autonomous systems via Poisson neural networks
Pengzhan Jin, Zhen Zhang, Ioannis G. Kevrekidis +1
We propose the Poisson neural networks (PNNs) to learn Poisson systems and trajectories of autonomous systems from data. Based on the Darboux-Lie theorem, the phase flow of a Poiss…