538 citations · 706 across the 12 of their papers we have counts for
5 papers · 1 filter
Efficient multistep methods for tempered fractional calculus: Algorithms and Simulations
Ling Guo, Fanhai Zeng, Ian Turner +2
In this work, we extend the fractional linear multistep methods in [C. Lubich, SIAM J. Math. Anal., 17 (1986), pp.704--719] to the tempered fractional integral and derivative opera…
Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems
Dongkun Zhang, Lu Lu, Ling Guo +1
Physics-informed neural networks (PINNs) have recently emerged as an alternative way of solving partial differential equations (PDEs) without the need of building elaborate grids,…
Stochastic collocation methods via minimization of Transformed penalty
Ling Guo, Jing Li, Yongle Liu
We study the properties of sparse reconstruction of transformed (TL1) minimization and present improved theoretical results about the recoverability and the accuracy of th…
Data-driven polynomial chaos expansions: a weighted least-square approximation
Ling Guo, Yongle Liu, Tao Zhou
In this work, we combine the idea of data-driven polynomial chaos expansions with the weighted least-square approach to solve uncertainty quantification (UQ) problems. The idea of…
A gradient enhanced -minimization for sparse approximation of polynomial chaos expansions
Ling Guo, Akil Narayan, Tao Zhou
We investigate a gradient-enhanced -minimization for constructing sparse polynomial chaos expansions. In addition to function evaluations, measurements of the function grad…