activity
20192022
most citedMulti-scale Deep Neural Network (MscaleDNN) Methods for Oscillatory Stokes Flows in Complex Domains

61 citations · 113 across the 7 of their papers we have counts for

collaborators
Showing math.NAShow all

5 papers · 1 filter

math.NA20228 cited

A Causality-DeepONet for Causal Responses of Linear Dynamical Systems

Lizuo Liu, Kamaljyoti Nath, Wei Cai

In this paper, we propose a DeepONet structure with causality to represent the causal linear operators between Banach spaces of time-dependent signals. The theorem of universal app…

math.NA20223 cited

DeepPropNet -- A Recursive Deep Propagator Neural Network for Learning Evolution PDE Operators

Lizuo Liu, Wei Cai

In this paper, we propose a deep neural network approximation to the evolution operator for time dependent PDE systems over long time period by recursively using one single neural…

math.NA202116 cited

Multiscale DeepONet for Nonlinear Operators in Oscillatory Function Spaces for Building Seismic Wave Responses

Lizuo Liu, Wei Cai

In this paper, we propose a multiscale DeepONet to represent nonlinear operator between Banach spaces of highly oscillatory continuous functions. The multiscale deep neural network…

math.NA2020

FBSDE based Neural Network Algorithms for High-Dimensional Quasilinear Parabolic PDEs

Wenzhong Zhang, Wei Cai

In this paper, we propose forward and backward stochastic differential equations (FBSDEs) based deep neural network (DNN) learning algorithms for the solution of high dimensional q…

math.NA202061 cited

Multi-scale Deep Neural Network (MscaleDNN) Methods for Oscillatory Stokes Flows in Complex Domains

Bo Wang, Wenzhong Zhang, Wei Cai

In this paper, we study a multi-scale deep neural network (MscaleDNN) as a meshless numerical method for computing oscillatory Stokes flows in complex domains. The MscaleDNN employ…