Fractional partial differential equations (FPDEs) can effectively repres...
In this paper, a novel framework is established for uncertainty
quantifi...
We introduce a sampling based machine learning approach, Monte Carlo phy...
We introduce in this work the normalizing field flows (NFF) for learning...
One of the open problems in the field of forward uncertainty quantificat...
Deep neural networks (DNNs) perform well on a variety of tasks despite t...
This paper presents the problems and solutions addressed at the JSALT
wo...
One of the open problems in scientific computing is the long-time integr...
The I4U consortium was established to facilitate a joint entry to NIST
s...
Physics-informed neural networks (PINNs) have recently emerged as an
alt...