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This paper presents a novel approach to rigorously solving initial value problems for semilinear parabolic partial differential equations (PDEs) using fully spectral Fourier-Chebyshev expansions. By reformulating the PDE as a system of…

Analysis of PDEs · Mathematics 2025-03-03 Matthieu Cadiot , Jean-Philippe Lessard

Recent advances in the theory of Neural Operators (NOs) have enabled fast and accurate computation of the solutions to complex systems described by partial differential equations (PDEs). Despite their great success, current NO-based…

Machine Learning · Computer Science 2024-03-18 Ashutosh Singh , Ricardo Augusto Borsoi , Deniz Erdogmus , Tales Imbiriba

In this paper we establish a connection between non-convex optimization methods for training deep neural networks and nonlinear partial differential equations (PDEs). Relaxation techniques arising in statistical physics which have already…

Machine Learning · Computer Science 2017-06-05 Pratik Chaudhari , Adam Oberman , Stanley Osher , Stefano Soatto , Guillaume Carlier

We provide necessary and sufficient conditions for stochastic invariance of finite dimensional submanifolds for solutions of stochastic partial differential equations (SPDEs) in continuously embedded Hilbert spaces with non-smooth…

Probability · Mathematics 2025-11-21 Rajeev Bhaskaran , Stefan Tappe

We consider the inverse problem of determining a general semilinear term appearing in nonlinear parabolic equations. For this purpose, we derive a new criterion that allows to prove global recovery of some general class of semilinear terms…

Analysis of PDEs · Mathematics 2020-11-13 Yavar Kian , Gunther Uhlmann

Under investigation is the problem of finding the best approximation of a function in a Hilbert space subject to convex constraints and prescribed nonlinear transformations. We show that in many instances these prescriptions can be…

Functional Analysis · Mathematics 2021-06-17 Patrick L. Combettes , Zev C. Woodstock

The coefficients in a second order parabolic linear stochastic partial differential equation (SPDE) are estimated from multiple spatially localised measurements. Assuming that the spatial resolution tends to zero and the number of…

Statistics Theory · Mathematics 2024-07-26 Randolf Altmeyer , Anton Tiepner , Martin Wahl

We introduce a generalized finite difference method for solving a large range of fully nonlinear elliptic partial differential equations in three dimensions. Methods are based on Cartesian grids, augmented by additional points carefully…

Numerical Analysis · Mathematics 2021-03-19 Brittany Froese Hamfeldt , Jacob Lesniewski

While approaches to model the progression of fracture have received significant attention, methods to find the solution to the associated nonlinear equations have not. In general, nonlinear solution methods and optimization methods have a…

Numerical Analysis · Mathematics 2025-02-28 Alberto Cattaneo , Varun Shankar , M. Keith Ballard

We revisit a unified methodology for the iterative solution of nonlinear equations in Hilbert spaces. Our key observation is that the general approach from [Heid & Wihler, Math. Comp. 89 (2020), Calcolo 57 (2020)] satisfies an energy…

Numerical Analysis · Mathematics 2021-02-18 Pascal Heid , Dirk Praetorius , Thomas P. Wihler

In this short note, we investigate simultaneous recovery inverse problems for semilinear elliptic equations with partial data. The main technique is based on higher order linearization and monotonicity approaches. With these methods at…

Analysis of PDEs · Mathematics 2022-12-13 Bastian Harrach , Yi-Hsuan Lin

We obtain a general concept of triplet of Hilbert spaces with closed (unbounded) embeddings instead of continuous (bounded) ones. The construction starts with a positive selfadjoint operator $H$, that is called the Hamiltonian of the…

Functional Analysis · Mathematics 2025-11-04 Petru Cojuhari , Aurelian Gheondea

This paper is concerned with model order reduction of parametric Partial Differential Equations (PDEs) using tree-based library approximations. Classical approaches are formulated for PDEs on Hilbert spaces and involve one single linear…

Numerical Analysis · Mathematics 2024-04-19 Diane Guignard , Olga Mula

This article investigates the non-stationary reaction-diffusion-advection equation, emphasizing solutions with internal layers and the associated inverse problems. We examine a nonlinear singularly perturbed partial differential equation…

Numerical Analysis · Mathematics 2025-02-06 Dmitrii Chaikovskii , Ye Zhang , Aleksei Liubavin

As the dimension of a system increases, traditional methods for control and differential games rapidly become intractable, making the design of safe autonomous agents challenging in complex or team settings. Deep-learning approaches avoid…

Optimization and Control · Mathematics 2025-04-29 William Sharpless , Zeyuan Feng , Somil Bansal , Sylvia Herbert

We introduce a simple, rigorous, and unified framework for solving nonlinear partial differential equations (PDEs), and for solving inverse problems (IPs) involving the identification of parameters in PDEs, using the framework of Gaussian…

Numerical Analysis · Mathematics 2021-08-12 Yifan Chen , Bamdad Hosseini , Houman Owhadi , Andrew M Stuart

We propose notions of minimax and viscosity solutions for a class of fully nonlinear path-dependent PDEs with nonlinear, monotone, and coercive operators on Hilbert space. Our main result is well-posedness (existence, uniqueness, and…

Analysis of PDEs · Mathematics 2018-07-24 Erhan Bayraktar , Christian Keller

In this paper, we investigate boundary estimates for the Dirichlet problem for a class of fully nonlinear elliptic equations with general boundary conditions, including nonzero boundary conditions. Given specific structural conditions on…

Analysis of PDEs · Mathematics 2025-07-29 Mengni Li , Chaofan Shi

In this paper convex optimization techniques are employed for convex optimization problems in infinite dimensional Hilbert spaces. A first order optimality condition is given. Let $f : \mathbb{R}^{n}\rightarrow \mathbb{R}$ and let $x\in…

Functional Analysis · Mathematics 2019-03-26 Benard Okelo

The full history recursive multilevel Picard approximation method for semilinear parabolic partial differential equations (PDEs) is the only method which provably overcomes the curse of dimensionality for general time horizons if the…

Numerical Analysis · Mathematics 2022-04-29 Martin Hutzenthaler , Tuan Anh Nguyen
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