Results 71 to 80 of about 82,072,160 (134)

Partial differential equations in data science. [PDF]

Philos Trans A Math Phys Eng Sci
Bertozzi AL, Drenska N, Latz J, Thorpe M.   +3 more
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

Sparse identification of nonlinear dynamics and Koopman operators with Shallow Recurrent Decoder Networks. [PDF]

Proc Natl Acad Sci U S A
Gao ML, Williams JP, Kutz JN.
europepmc   +1 more source

Non-smooth variational problems and applications. [PDF]

Philos Trans A Math Phys Eng Sci, 2022
Kovtunenko VA, Itou H, Khludnev AM, Rudoy EM.   +3 more
europepmc   +1 more source

Hybridndiff-UQ: Uncertainty quantification for hybrid neural differentiable modeling. [PDF]

Theor Appl Mech Lett
Akhare D, Luo T, Wang JX.
europepmc   +1 more source

Determinism, well-posedness, and applications of the ultrahyperbolic wave equation in spacekime. [PDF]

Partial Differ Equ Appl Math, 2022
Wang Y, Shen Y, Deng D, Dinov ID.
europepmc   +1 more source

Information-distilled physics informed deep learning for high order differential inverse problems with extreme discontinuities. [PDF]

Commun Eng
Peng M, Tang H.
europepmc   +1 more source

A PINN-driven game-theoretic framework in limited data photoacoustic tomography. [PDF]

Inverse Probl
Roy S, Pal S.
europepmc   +1 more source

An Attention-based Spatio-Temporal Neural Operator for Evolving Physics. [PDF]

Mach Learn Sci Technol
Karkaria V, Lee D, Chen YP, Yu Y, Chen W.   +4 more
europepmc   +1 more source

WF-PINNs: solving forward and inverse problems of burgers equation with steep gradients using weak-form physics-informed neural networks. [PDF]

Sci Rep
Wang X, Yi S, Gu H, Xu J, Xu W.
europepmc   +1 more source