Results 151 to 160 of about 987 (227)

A physics-informed neural network approach for estimating population-level pharmacokinetic parameters from aggregated concentration data. [PDF]

J Pharmacokinet Pharmacodyn
Tsiros P, Minadakis V, Sarimveis H.
europepmc   +1 more source

A novel simulation-based analysis of a stochastic HIV model with the time delay using high order spectral collocation technique. [PDF]

Sci Rep
Khan SU, Ullah S, Li S, Mostafa AM, Bilal Riaz M, AlQahtani NF, Teklu SW.   +6 more
europepmc   +1 more source

A Random Differential Equation Approach for Modeling the Growth of Microalgae in Photobioreactors. [PDF]

Bull Math Biol
Andreu-Vilarroig C, Cortés JC, Navarro-Quiles A, Papáček Š, Pérez CL.   +4 more
europepmc   +1 more source

Accelerated computation for 2D isogeometric acoustic model with ground reflection by integrating Taylor expansion and deep neural network. [PDF]

Sci Prog
Gao J, Ma H, Miao D, Yao R, Zhang Y.
europepmc   +1 more source

Surrogate model-based multi-objective Bayesian optimisation of porous acoustic barriers. [PDF]

Eng Comput
Liravi H, Bécot FX, Kaewunruen S, Ninić J.   +3 more
europepmc   +1 more source

Numerical simulation of a fractional stochastic delay differential equations using spectral scheme: a comprehensive stability analysis. [PDF]

Sci Rep
Li S, Khan SU, Riaz MB, AlQahtani SA, Alamri AM.   +4 more
europepmc   +1 more source

Physics-informed deep learning quantifies propagated uncertainty in seismic structure and hypocenter determination. [PDF]

Sci Rep
Agata R, Shiraishi K, Fujie G.
europepmc   +1 more source

A variational framework for residual-based adaptivity in neural PDE solvers and operator learning. [PDF]

NPJ Artif Intell
Toscano JD, Chen DT, Ooomen V, Darbon J, Karniadakis GE.   +4 more
europepmc   +1 more source

Scaling of Intrusive Stochastic Collocation and Stochastic Galerkin Methods for Uncertainty Quantification in Monte Carlo Particle Transport.

, 2015
Aaron Olson, Brian Claude Franke, Anil K. Prinja   +2 more
openalex   +1 more source

A deep learning approach: physics-informed neural networks for solving a nonlinear telegraph equation with different boundary conditions. [PDF]

BMC Res Notes
Deresse AT, Bekela AS.
europepmc   +1 more source