Transfer learning for partial differential equations (PDEs) is to develo...
This paper is concerned with conditionally structure-preserving, low
reg...
In this paper, we propose and analyze a linear second-order numerical me...
The convective Allen-Cahn equation has been widely used to simulate
mult...
In this paper, we propose an efficient exponential integrator finite ele...
A method for the multifidelity Monte Carlo (MFMC) estimation of statisti...
The metriplectic formalism is useful for describing complete dynamical
s...
It is well-known that the Allen-Cahn equation not only satisfies the ene...
The energy dissipation law and the maximum bound principle (MBP) are two...
In this paper, we tackle the problem of one-shot unsupervised domain
ada...
Due to the curse of dimensionality and the limitation on training data,
...
The popularity of deep convolutional autoencoders (CAEs) has engendered
...
It is well known that the classic Allen-Cahn equation satisfies the maxi...
In order to treat the multiple time scales of ocean dynamics in an effic...
Partial differential equations are often used to model various physical
...
A dimension reduction method based on the "Nonlinear Level set Learning"...
Semantic segmentation of nighttime images plays an equally important rol...
Maximum bound principle (MBP) is an important property for a large class...
A large class of semilinear parabolic equations satisfy the maximum boun...
The ubiquity of semilinear parabolic equations has been illustrated in t...
In this paper, the diagonal sweeping domain decomposition method (DDM) f...
In this paper, we propose a novel diagonal sweeping domain decomposition...
A new energy and enstrophy conserving scheme is evaluated using a suite ...
Binary image segmentation plays an important role in computer vision and...