The physics informed neural networks (PINNs) has been widely utilized to...
In this letter, we revisit the IEQ method and provide a new perspective ...
The scalar auxiliary variable (SAV) method was introduced by Shen et al....
This letter revisits the energy quadratization (EQ) method by introducin...
The Cahn-Hilliard-Navier-Stokes (CHNS) equations represent the fundament...
In this paper, we present a general numerical platform for designing
acc...
Model discovery based on existing data has been one of the major focuses...
Phase field models, in particular, the Allen-Cahn type and Cahn-Hilliard...
In this paper, we introduce a new deep learning framework for discoverin...
In this paper, a non-uniform time-stepping convex-splitting numerical
al...
We present a paradigm for developing arbitrarily high order, linear,
unc...
We present a systematical approach to developing arbitrarily high order,...
In this paper, we propose a novel family of high-order numerical schemes...
The results from Genome-Wide Association Studies (GWAS) on thousands of
...