This paper explores the imperative need and methodology for developing a...
We propose a novel training algorithm called DualFL (Dualized Federated
...
By investigating iterative methods for a constrained linear model, we pr...
In this paper, we propose a novel algorithm called Neuron-wise Parallel
...
Neural networks are universal function approximators which are known to
...
In this paper, we revisit Korn's inequality for the piecewise H^1 space
...
In this paper, we propose a new finite element approach to simulate the
...
We propose a constrained linear data-feature-mapping model as an
interpr...
This paper is devoted to establishing L^2 approximation properties for d...
Modeling the microstructure evolution of a material embedded in a device...
Recently, neural networks have been widely applied for solving partial
d...
We consider the variation space corresponding to a dictionary of functio...
We analyze the orthogonal greedy algorithm when applied to dictionaries
...
We consider the approximation rates of shallow neural networks with resp...
We study ReLU deep neural networks (DNNs) by investigating their connect...
Methods for solving PDEs using neural networks have recently become a ve...
We propose and analyze a robust BPX preconditioner for the integral
frac...
This article addresses several fundamental issues associated with the
ap...
For the Hodge–Laplace equation in finite element exterior calculus, we
i...
We study the approximation properties of shallow neural networks (NN) wi...
This paper studies numerical solutions for parameterized partial differe...
We study a family of H^m-conforming piecewise polynomials based on
artif...
Pruning the weights of neural networks is an effective and widely-used
t...
We construct finite element methods for the magnetohydrodynamics (MHD) s...
In this paper, we propose and analyze an abstract stabilized mixed finit...
This paper presents an extended Galerkin analysis for various Galerkin
m...
In this paper we study the linear systems arising from discretized
poroe...
In this paper, we propose a constrained linear data-feature mapping mode...
Pulse feeling, representing the tactile arterial palpation of the heartb...
A general framework, known as extended Galerkin method, is presented in ...
We prove two new results concerning the approximation properties of neur...
We develop a unified model, known as MgNet, that simultaneously recovers...
We proposed a modified regularized dual averaging method for training sp...