Physics-informed machine learning and inverse modeling require the solut...
ADCME is a novel computational framework to solve inverse problems invol...
We propose a framework for training neural networks that are coupled wit...
Inverse problems in fluid dynamics are ubiquitous in science and enginee...
We propose a novel approach to model viscoelasticity materials using neu...
We present the Cholesky-factored symmetric positive definite neural netw...
Deep neural networks (DNN) have been used to model nonlinear relations
b...
Many engineering problems involve learning hidden dynamics from indirect...
Many scientific and engineering applications are formulated as inverse
p...
The Lévy process has been widely applied to mathematical finance, quantu...