Results 61 to 70 of about 85,369,012 (181)
Relative Arbitrage Opportunities With Interactions Among N Investors
Mathematical Finance, EarlyView.ABSTRACT The relative arbitrage portfolio outperforms a benchmark portfolio over a given time‐horizon with probability one. With market price of risk processes depending on the market portfolio and investors, this paper analyzes the multi‐agent optimization of relative arbitrage opportunities in the coupled system of market and wealth dynamics.
Tomoyuki Ichiba, Nicole Tianjiao Yang
wiley +1 more source
Mathematical Finance, EarlyView.ABSTRACT We extend the notion of forward performance criteria to settings with random endowment in incomplete markets. Building on these results, we introduce and develop the novel concept of forward optimized certainty equivalent (forward OCE), which offers a genuinely dynamic valuation mechanism that accommodates progressively adaptive market model ...
Gechun Liang +2 more
wiley +1 more source
The Hadamard-PINN for PDE inverse problems: Convergence with distant initial guesses
Examples and CounterexamplesThis paper presents the Hadamard-Physics-Informed Neural Network (H-PINN) for solving inverse problems in partial differential equations (PDEs), specifically the heat equation and the Korteweg–de Vries (KdV) equation.
Yohan Chandrasukmana +2 more
doaj +1 more source
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 4, December 2026.ABSTRACT Recent results have shown that domain‐uniform stabilizability and detectability imply spatial exponential decay of perturbations in optimally controlled hyperbolic PDEs on one‐dimensional domains. This domain‐uniform stabilizability and detectability can be achieved only if the control domain is distributed over the whole spatial domain such ...
Benedikt Oppeneiger
wiley +1 more source
Inverse Problems for Semilinear Wave Equations on Lorentzian Manifolds [PDF]
, 2018 We consider inverse problems in space-time (M, g), a 4-dimensional Lorentzian manifold. For semilinear wave equations square(g)u + H (x, u) = f, where square(g) denotes the usual Laplace-Beltrami operator, we prove that the source-to-solution map , L : f
Matti Lassas +5 more
core +1 more source
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 4, December 2026.ABSTRACT Stochastic Galerkin methods offer unexplored potential for the numerical simulation of parabolic problems with random variables, in particular if they are combined with variational discretizations of the space and time variables. Due to the high dimensionality, the solution of the arising algebraic systems do not become feasible without ...
Moataz Dawor +2 more
wiley +1 more source
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 4, December 2026.ABSTRACT We develop a physics‐informed Fourier Neural Operator (PINO) for the surrogate modeling of full‐field responses in polycrystalline microstructures. Reference stress and strain fields are generated using an FFT‐based full‐field solver under prescribed macroscopic loading. The model maps the crystallographic orientation field q(x)$\bm{q}(\bm{x})$
Ahmad Awad, Lisa Scheunemann
wiley +1 more source
Efficient MCMC and posterior consistency for Bayesian inverse problems [PDF]
Many mathematical models used in science and technology often contain parameters that are not known a priori. In order to match a model to a physical phenomenon, the parameters have to be adapted on the basis of the available data.
Vollmer, Sebastian
core
Stochastic PDEs with multiscale structure [PDF]
, 2012 We study the spatial homogenisation of parabolic linear stochastic PDEs exhibiting a two-scale structure both at the level of the linear operator and at the level of the Gaussian driving noise.
Martin Hairer +4 more
core +1 more source
Data-Centric EngineeringWe propose a physics-constrained convolutional neural network (PC-CNN) to solve two types of inverse problems in partial differential equations (PDEs), which are nonlinear and vary both in space and time.
Daniel Kelshaw, Luca Magri
doaj +1 more source