Results 41 to 50 of about 723 (140)

Solving inverse Gardner–Kawahara problems with physics-informed neural networks: a data-driven approach

Physica Scripta
Inverse problems involving nonlinear partial differential equations (PDEs) pose significant challenges due to their ill-posed nature and reliance on sparse or noisy observations.
Mazaher Kabiri, Sanam Sabooni
semanticscholar   +1 more source

Counting Degrees of Freedom: A Method Applicable From Scalars to f(Q)$f(\mathbb {Q})$ Gravity and Beyond

Fortschritte der Physik, Volume 74, Issue 6, June 2026.
ABSTRACT We present a clear, step‐by‐step method for counting degrees of freedom and identifying constraints in general field theories. This approach, grounded in the works of Einstein, Hilbert, Cartan, Kuranishi, and, more recently, Seiler, is neither Lagrangian nor Hamiltonian in nature. Instead, it applies directly to the field equations. We offer a
Lavinia Heisenberg
wiley   +1 more source

Well‐Posed and Ill‐Posed Boundary Value Problems for PDE [PDF]

Abstract and Applied Analysis, 2012
Ashyralyev, Allaberen, Piskarev, Sergey, Covachev, Valery, Ashurov, Ravshan, Yurtsever, Hasan Ali   +4 more
openaire   +3 more sources

Sequential bi-level regularized inversion with application to hidden reaction law discovery [PDF]

Inverse Problems
In this article, we develop and present a novel regularization scheme for ill-posed inverse problems governed by nonlinear time-dependent partial differential equations (PDEs). In our recent work, we introduced a bi-level regularization framework.
Tram Thi Ngoc Nguyen
semanticscholar   +1 more source

A Novel Variational Quantum Algorithm for Solving High-Dimensional Partial Differential Equations in Climate Modeling

Journal of Applied Automation Technologies
This paper proposes a variational quantum algorithm to address the large-scale and low computational efficiency issues of high-dimensional partial differential equations (PDEs) in climate science. In this method, parameterized quantum circuits encode the
Marcin Eryk Gierak, Henryk Kasprzak, Feliks Karpiński   +2 more
semanticscholar   +1 more source

On level set regularization for highly ill-posed distributed parameter estimation problems

Journal of Computational Physics, 2006
K. V. D. Doel, U. Ascher
semanticscholar   +1 more source

Data-driven, ML-assisted approaches to problem well-posedness. [PDF]

PNAS Nexus
Bertalan T, Kevrekidis GA, Koronaki ED, Mishra S, Rebrova E, Kevrekidis IG.   +5 more
europepmc   +1 more source

The finite element neural network method to simulate two dimensional partial differential equations and perform parameter identification. [PDF]

Sci Rep
Abda M, Berthet L, Hamedi M, Hibatullah D, Piollet E, Blake C, Blais B, Gosselin FP.   +7 more
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

Simultaneous Numerical Determination of Two Time-dependent Coefficients in Second Order Parabolic Equation With Nonlocal Initial and Boundary Conditions. [PDF]

F1000Res
A J Al-Shatrah M, Sabah Hussein M.
europepmc   +1 more source