Results 171 to 180 of about 1,546 (231)

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

Hybrid physics-informed artificial intelligence for high-fidelity modeling and optimization of electrical systems. [PDF]

Front Artif Intell
Nyangon J.
europepmc   +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

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

Hysteresis in cavitation emissions during a ramped-then-deramped amplitude sonication: A theoretical and experimental investigation. [PDF]

Nonlinear Dyn
Zhang Y, Li S, Prentice P, Cammarano A.
europepmc   +1 more source

Employing variance component estimation for point cloud based geometric surface representation by B-splines. [PDF]

J Appl Geod
Ötsch E, Harmening C, Neuner H.
europepmc   +1 more source

A primer on variational inference for physics-informed deep generative modelling. [PDF]

Philos Trans A Math Phys Eng Sci
Glyn-Davies A, Vadeboncoeur A, Akyildiz OD, Kazlauskaite I, Girolami M.   +4 more
europepmc   +1 more source

Moving from table to graph in physics-informed spatio-temporal symbolic regression. [PDF]

Sci Rep
Lazebnik T, Liberzon A.
europepmc   +1 more source

Computational analysis of a class of singular nonlinear fractional multi-order heat conduction model of the human head. [PDF]

Sci Rep
Izadi M, Atangana A.
europepmc   +1 more source

Investigating the use of physics informed neural networks for dam-break scenarios. [PDF]

PLoS One
Mumtaz K, Nadeem MW, Khan A, Lakdawala Z.   +3 more
europepmc   +1 more source