Results 21 to 30 of about 315 (88)
International Journal for Numerical Methods in Engineering, Volume 127, Issue 15, 15 August 2026.ABSTRACT This study introduces the inductive differential constraint method (IDCM), a data‐informed structural regularization framework that enhances neural network predictions under data‐scarce regimes by enforcing invariant differential structures extracted from simulation data.
Rekisei Ozawa, Yoshitaka Wada
wiley +1 more source
Invariant Measure and Universality of the 2D Yang–Mills Langevin Dynamic
Communications on Pure and Applied Mathematics, Volume 79, Issue 8, Page 1973-2102, August 2026.ABSTRACT We prove that the Yang–Mills (YM) measure for the trivial principal bundle over the two‐dimensional torus, with any connected, compact structure group, is invariant for the associated renormalised Langevin dynamic. Our argument relies on a combination of regularity structures, lattice gauge‐fixing and Bourgain's method for invariant measures ...
Ilya Chevyrev, Hao Shen
wiley +1 more source
Gradient‐Free Online Learning of Subgrid‐Scale Dynamics With Neural Emulators
Journal of Advances in Modeling Earth Systems, Volume 18, Issue 8, August 2026.Abstract In this paper, we propose a generic algorithm to train machine learning‐based subgrid parametrizations online, that is, with a posteriori loss functions, but for non‐differentiable numerical solvers. The proposed approach leverages a neural emulator to approximate the reduced state‐space solver, which is then used to allow gradient propagation
H. Frezat +3 more
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Mechanistic‐Statistical Inference of Mosquito Dynamics From Mark‐Release‐Recapture Data
Population Ecology, Volume 68, Issue 3, July 2026.Mark‐release‐recapture data contain valuable information on mosquito dispersal and survival, but this information is only indirectly observed through trap counts. We combine a mechanistic diffusion model with a statistical observation model to infer movement, mortality, and trap efficiency jointly.
Nga Nguyen +4 more
wiley +1 more source
Local Polynomial Regression and Filtering for a Versatile Mesh‐Free PDE Solver
International Journal for Numerical Methods in Fluids, Volume 98, Issue 7, Page 804-839, July 2026.A high‐order, mesh‐free finite difference method for solving differential equations is presented. Both derivative approximation and scheme stabilisation is carried out by parametric or non‐parametric local polynomial regression, making the resulting numerical method accurate, simple and versatile. Numerous numerical benchmark tests are investigated for
Alberto M. Gambaruto
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Numerical Methods for Partial Differential Equations, Volume 42, Issue 4, July 2026.ABSTRACT The main purpose of this paper is to design a fully discrete local discontinuous Galerkin (LDG) scheme for the generalized Benjamin–Ono equation. First, we prove the L2$$ {L}^2 $$‐stability for the proposed semi‐discrete LDG scheme and obtained a suboptimal order of convergence for power nonlinear flux.
Mukul Dwivedi, Tanmay Sarkar
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An Algebraic Study of Parametric Stokes Phenomena
Studies in Applied Mathematics, Volume 157, Issue 1, July 2026.ABSTRACT We investigate geometric aspects of co‐equational parametric resurgence, by studying physical problems whose formal asymptotic solutions give rise to Borel transforms lying on an algebraic curve. This perspective allows us to elucidate concepts unique to parametric resurgence such as singularity structures, (virtual) turning points, and the ...
Inês Aniceto, Samuel Crew
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Experimental Physiology, Volume 111, Issue 7, Page 3267-3279, 1 July 2026.Abstract This study investigated cerebral and neuromuscular responses to three exercise models: time trial (TT), maximal oxygen uptake (V̇O2max${{\dot{V}}_{{{{\mathrm{O}}}_2}{\mathrm{max}}}}$) and time to exhaustion (TTE). Fourteen participants completed the tests in the following order: V̇O2max${{\dot{V}}_{{{{\mathrm{O}}}_2}{\mathrm{max}}}}$, TT and ...
Caroline V. Robertson +3 more
wiley +1 more source
Nonlinear SPDEs and Maximal Regularity: An Extended Survey. [PDF]
Nonlinear Differ Equ ApplAgresti A, Veraar M.
europepmc +1 more source
Deterministic, stochastic, and mean-field PDE models in neuroscience. [PDF]
Front Comput NeurosciÇetin C +5 more
europepmc +1 more source