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Showing 1389 results for "artificial intelligence" in Mathematics
Mathematics Preprint PDF DOI

On three-dimensional flows of thermo-viscoelastic fluids of Giesekus type

Miroslav Bulicek, Tomas Los, Jakub Woznicki ยท 2026

Viscoelastic rate-type fluid models constitute a fundamental framework for the mathematical description of complex materials exhibiting coupled elastic and viscous effects, with a wide range of applicโ€ฆ

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Mathematics Preprint PDF DOI

h-Adaptive FV Subcell Shock-Capturing for DGSEM on Heterogeneous Curvilinear Meshes

Anna Schwarz, Jens Keim, Christian Rohde, Andrea Beck ยท 2026

High-order methods offer superior dispersion and dissipation properties compared to low-order schemes but require robust stabilization for discontinuities. To ensure stability, local artificial viscosโ€ฆ

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Mathematics Preprint PDF DOI

Explainable Artificial Intelligence for Financial Integral Equations: A Fixed-Point Neural Operator Approach

Sanjay Kumar Mohanty ยท 2026

The explainable artificial intelligence is used to analyze the stochastic Fredholm integral equations (SFIEs) and stochastic deep neural networks (SDNNs). The neural operator-based stochastic fixed poโ€ฆ

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Mathematics Preprint PDF DOI

Self-organized regime switching in null-recurrent dynamics

Johannes Brutsche, Sebastian Hahn, Angelika Rohde ยท 2026

Based on discrete observations $X_0,X_{\Delta},\dots, X_{n\Delta}$ for $\Delta=n^{-\gamma}$ with $\gamma\in [0,1)$ of the null-recurrent dynamic $dX_t = \sigma(X_t)dW_t$ with a Brownian motion $W$ andโ€ฆ

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Mathematics Preprint PDF DOI

Enforcing TSP-Optimality in Fair Vehicle Routing by Cutting Planes

Bart van Rossum, Rui Chen, Andrea Lodi ยท 2026

We study the fair capacitated vehicle routing problem, in which a fleet of vehicles must serve a set of customers such that the difference between the longest and shortest route, the range, is minimizโ€ฆ

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Mathematics Preprint PDF DOI

Nonconforming virtual element method for the Monge-Amp\`ere equation

Scott Congreve, Alice Hodson, Anwesh Pradhan ยท 2026

In this article, we develop the $C^1$-nonconforming $C^0$-conforming virtual element method (VEM) for the vanishing moment approximation of the second-order fully nonlinear Monge-Amp\`ere equation in โ€ฆ

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Mathematics Preprint PDF DOI

Local error estimates for a finite element method combining linear and nonlinear stabilization for the linear hyperbolic transport equation

Erik Burman, Fabian Heimann ยท 2026

In this paper, we investigate the combination of a linear continuous interior penalty type and a non-linear artificial diffusion stabilisation applied to the transport problem, based on continuous Galโ€ฆ

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Mathematics Preprint PDF DOI

Accuracy and stability of Artificial Neural Networks for HP-Splines frequency parameter selection

Vittoria Bruni, Paola Erminia Calabrese, Rosanna Campagna, Domenico Vitulano ยท 2026

This paper explores the use of artificial neural networks for the stable and data-driven selection of the frequency parameter in hyperbolic polynomial penalized splines (HP-splines). This parameter deโ€ฆ

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Mathematics Preprint PDF DOI

Indirect Prey-taxis VS a Shortwave External Signal in Multiple Dimensions

Andrey Morgulis, Karrar Malal ยท 2026

We address a short-wave asymptotic for one class of quasi-linear second order PDE systems involving the cross-diffusion described by the so-called Patlak--Keller--Segel law. It is common to employ theโ€ฆ

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Mathematics Preprint PDF DOI

Mapping-based Hard-constrained Physics-Informed Neural Networks for unbounded wave problems

Tao Zhang, Hanshu Chen, Ilia Marchevsky, Zhuojia Fu ยท 2026

The aim of this paper is to introduce a Mapping-based Hard-constrained Physics-Informed Neural Network (MH-PINN) for efficiently and accurately solving unbounded wave problems. First, we propose a cooโ€ฆ

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Mathematics Preprint PDF DOI

Dual formulations of geometric curvature flows and their discretizations

Guangwei Gao, Buyang Li, Rong Tang ยท 2026

We propose new formulations of geometric curvature flows -- referred to as \emph{dual formulations} -- that are equivalent to the original formulations but provide a novel framework for constructing lโ€ฆ

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Mathematics Preprint PDF DOI

DeepRitzSplit Neural Operator for Phase-Field Models via Energy Splitting

Chih-Kang Huang, Ludovick Gagnon, Miha Zaloznik, Benoit Appolaire ยท 2026

The multi-scale and non-linear nature of phase-field models of solidification requires fine spatial and temporal discretization, leading to long computation times. This could be overcome with artificiโ€ฆ

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Mathematics Preprint PDF DOI

Optimal Linear Interpolation under Differential Information: application to the prediction of perfect flows

Soumyodeep Mukhopadhyay (Mines Saint-Etienne MSE, FAYOL-ENSMSE, FAYOL-ENSMSE, LIMOS), Didier Rulliere (Mines Saint-Etienne MSE, FAYOL-ENSMSE, LIMOS, FAYOL-ENSMSE), Rodolphe Le Riche (LIMOS, UCA [2017-2020], ENSM ST-ETIENNE, CNRS), David Gaudrie, Xavier Bay (FAYOL-ENSMSE, LIMOS, Mines Saint-Etienne MSE), Laurent Genest, David Gaudrie ยท 2026

Approximation of functions satisfying partial differential equations (PDEs) is paramount for simulation of physical fluid flows and other problems in physics. Recently, physics-informed machine learniโ€ฆ

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Mathematics Preprint PDF DOI

Stably Determining a generalised Impedance Obstacle from a Single Far-Field Pattern

Huaian Diao, Hongyu Liu, Longyue Tao ยท 2026

Inverse scattering focuses on recovering unknown scatterers from wave measurements. A fundamental challenge is determining whether an inverse obstacle problem can be resolved from a single far-field mโ€ฆ

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Mathematics Preprint PDF DOI

Deep Learning for Sequential Decision Making under Uncertainty: Foundations, Frameworks, and Frontiers

I. Esra Buyuktahtakin ยท 2026

Artificial intelligence (AI) is moving increasingly beyond prediction to support decisions in complex, uncertain, and dynamic environments. This shift creates a natural intersection with operations reโ€ฆ

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Mathematics Preprint PDF DOI

Policy Iteration for Stationary Discounted Hamilton--Jacobi--Bellman Equations: A Viscosity Approach

Namkyeong Cho, Yeoneung Kim ยท 2026

We study policy iteration (PI) for deterministic infinite-horizon discounted optimal control problems, whose value function is characterized by a stationary Hamilton--Jacobi--Bellman (HJB) equation. Aโ€ฆ

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Mathematics Preprint PDF DOI

Effective Dynamics and Transition Pathways from Koopman-Inspired Neural Learning of Collective Variables

Alexander Sikorski, Luca Donati, Marcus Weber, Christof Schutte ยท 2026

The ISOKANN (Invariant Subspaces of Koopman Operators Learned by Artificial Neural Networks) framework provides a data-driven route to extract collective variables (CVs) and effective dynamics from coโ€ฆ

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Mathematics Preprint PDF DOI

Robust $\mathcal{H}_\infty$ Observer Design via Finsler's Lemma and IQCs

Raktim Bhattacharya, Felix Biertumpfel ยท 2026

This paper develops a Finsler-based LMI for robust $\mathcal{H}_\infty$ observer design with integral quadratic constraints (IQCs) and block-structured uncertainty. By introducing a slack variable thaโ€ฆ

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Mathematics Preprint PDF DOI

Entropy correction artificial viscosity for high order DG methods using multiple artificial viscosities

Raymond Park, Jesse Chan ยท 2026

Entropy stable discontinuous Galerkin (DG) methods display improved robustness for problems with shocks, turbulence, and under-resolved features by enforcing an entropy inequality. Such methods have tโ€ฆ

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Mathematics Preprint PDF DOI

Error Estimates of the Gain Approximation by Hermite-Galerkin Method in Feedback Particle Filter

Ruoyu Wang, Peng Sun, Xue Luo ยท 2026

The feedback particle filter (FPF) is a promising nonlinear filtering (NLF) method, but its practical implementation is hindered by the intractability of the gain function, which satisfies a boundary โ€ฆ

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