In this paper, we introduce a new family of orthogonal systems, termed a...
In the study of subsurface seismic imaging, solving the acoustic wave
eq...
This paper applies an idea of adaptive momentum for the nonlinear conjug...
In this work we aim to develop a unified mathematical framework and a
re...
In this paper we present an asymptotically compatible meshfree method fo...
The solvation free energy of organic molecules is a critical parameter i...
In this paper, we show a physics-informed neural network solver for the
...
This paper proposes a combination of rotational compressive sensing with...
Various noise models have been developed in quantum computing study to
d...
We provide a rigorous theoretical foundation for incorporating data of
o...
We propose a data fusion method based on multi-fidelity Gaussian process...
Gaussian Process (GP) regression is a flexible non-parametric approach t...
In this work, we propose a framework that combines the
approximation-the...
In this work, we propose a new Gaussian process regression (GPR)-based
m...
In this work, we propose a new Gaussian process regression (GPR) method:...
Compressive sensing has become a powerful addition to uncertainty
quanti...