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Inverse design of morphing slender structures with programmable curvature has significant applications in various engineering fields. Most existing studies formulate it as an optimization problem, which requires repeatedly solving the…

Soft Condensed Matter · Physics 2025-08-28 JiaHao Li , Weicheng Huang , YinBo Zhu , Luxia Yu , Xiaohao Sun , Mingchao Liu , HengAn Wu

We establish local existence and a quasi-optimal error estimate for piecewise cubic minimizers to the bending energy under a discretized inextensibility constraint. In previous research a discretization is used where the inextensibility…

Numerical Analysis · Mathematics 2025-09-03 Sören Bartels , Balázs Kovács , Dominik Schneider

A simple yet efficient computational algorithm for computing the continuous optimal experimental design for linear models is proposed. An alternative proof the monotonic convergence for $D$-optimal criterion on continuous design spaces are…

Computation · Statistics 2018-04-10 Jiangtao Duan , Wei Gao , Hon Keung Tony Ng

We investigate constrained optimal control problems for linear stochastic dynamical systems evolving in discrete time. We consider minimization of an expected value cost over a finite horizon. Hard constraints are introduced first, and then…

Optimization and Control · Mathematics 2011-07-07 Eugenio Cinquemani , Mayank Agarwal , Debasish Chatterjee , John Lygeros

We present a unified treatment of the abstract problem of finding the best approximation between a cone and spheres in the image of affine transformations. Prominent instances of this problem are phase retrieval and source localization. The…

Optimization and Control · Mathematics 2020-03-26 D. Russell Luke , Shoham Sabach , Marc Teboulle

We introduce a continuous domain framework for the recovery of a planar curve from a few samples. We model the curve as the zero level set of a trigonometric polynomial. We show that the exponential feature maps of the points on the curve…

Signal Processing · Electrical Eng. & Systems 2020-01-08 Qing Zou , Sunrita Poddar , Mathews Jacob

We are interested in the optimization of convex domains under a PDE constraint. Due to the difficulties of approximating convex domains in $\mathbb{R}^3$, the restriction to rotationally symmetric domains is used to reduce shape…

Optimization and Control · Mathematics 2022-06-13 Hedwig Keller , Sören Bartels , Gerd Wachsmuth

Convex regression is a promising area for bridging statistical estimation and deterministic convex optimization. New piecewise linear convex regression methods are fast and scalable, but can have instability when used to approximate…

Machine Learning · Computer Science 2012-06-22 Lauren Hannah , David Dunson

We learn parameterized nonlinear elasticity on curved surfaces using a physics-informed neural network that enforces governing equations and boundary conditions directly through the loss function, enabling a single trained model to…

Biological Physics · Physics 2026-04-15 Yankang Liu , Ke Zhang , Maziar Raissi , Roya Zandi

This paper introduces a new mathematical formulation and numerical approach for the computation of distances and geodesics between immersed planar curves. Our approach combines the general simplifying transform for first-order elastic…

Computational Geometry · Computer Science 2025-01-07 Yashil Sukurdeep , Martin Bauer , Nicolas Charon

The paper extends the formulation of a 2D geometrically exact beam element proposed in our previous paper [1] to curved elastic beams. This formulation is based on equilibrium equations in their integrated form, combined with the kinematic…

Computational Engineering, Finance, and Science · Computer Science 2022-10-06 Martin Horák , Emma La Malfa Ribolla , Milan Jirásek

We study computational and statistical consequences of problem geometry in stochastic and online optimization. By focusing on constraint set and gradient geometry, we characterize the problem families for which stochastic- and…

Optimization and Control · Mathematics 2025-07-17 Chen Cheng , Daniel Levy , John C. Duchi

Invariant manifolds are important constructs for the quantitative and qualitative understanding of nonlinear phenomena in dynamical systems. In nonlinear damped mechanical systems, for instance, spectral submanifolds have emerged as useful…

Computational Engineering, Finance, and Science · Computer Science 2021-10-15 Shobhit Jain , George Haller

Ordinary differential equations (ODEs) are widely used to model biological, (bio-)chemical and technical processes. The parameters of these ODEs are often estimated from experimental data using ODE-constrained optimisation. This article…

Optimization and Control · Mathematics 2015-11-06 Anna Fiedler , Fabian J. Theis , Jan Hasenauer

We consider the problem of finding curves of minimum pointwise-maximum curvature, i.e., curves of minimax curvature, among planar curves of fixed length with prescribed endpoints and tangents at the endpoints. We reformulate the problem in…

Optimization and Control · Mathematics 2024-04-22 C. Yalçın Kaya , Lyle Noakes , Philip Schrader

Differential equations (DE) constrained optimization plays a critical role in numerous scientific and engineering fields, including energy systems, aerospace engineering, ecology, and finance, where optimal configurations or control…

Machine Learning · Computer Science 2024-10-03 Vincenzo Di Vito , Mostafa Mohammadian , Kyri Baker , Ferdinando Fioretto

We investigate the equilibrium configurations of closed planar elastic curves of fixed length, whose stiffness, also known as the bending rigidity, depends on an additional density variable. The underlying variational model relies on the…

Analysis of PDEs · Mathematics 2021-10-14 Katharina Brazda , Gaspard Jankowiak , Christian Schmeiser , Ulisse Stefanelli

We construct a structure preserving non-conforming finite element approximation scheme for the bi-harmonic wave maps into spheres equation. It satisfies a discrete energy law and preserves the non-convex sphere constraint of the continuous…

Numerical Analysis · Mathematics 2026-04-09 Ľubomír Baňas , Sebastian Herr

A method is devised for numerically solving a class of finite-horizon optimal control problems subject to cascade linear discrete-time dynamics. It is assumed that the linear state and input inequality constraints, and the quadratic measure…

Optimization and Control · Mathematics 2017-10-13 Michael Cantoni , Farhad Farokhi , Eric C. Kerrigan , Iman Shames

We propose new sequential simulation-optimization algorithms for general convex optimization via simulation problems with high-dimensional discrete decision space. The performance of each choice of discrete decision variables is evaluated…

Optimization and Control · Mathematics 2022-02-15 Haixiang Zhang , Zeyu Zheng , Javad Lavaei