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Shape-constrained inference has wide applicability in bioassay, medicine, economics, risk assessment, and many other fields. Although there has been a large amount of work on monotone-constrained univariate curve estimation, multivariate…

Methodology · Statistics 2019-11-19 Lizhen Lin , Brian St. Thomas , Walter W. Piegorsch , James Scott , Carlos Carvalho

We develop and analyze a highly efficient, second-order time-marching scheme for infinite-dimensional nonlinear geophysical fluid models, designed to accurately approximate invariant measures-that is, the stationary statistical properties…

Numerical Analysis · Mathematics 2025-10-08 Daozhi Han , Xiaoming Wang

In Hamiltonian systems subjected to periodic perturbations the stable and unstable manifolds of the unstable periodic orbits provide the dynamical "skeleton" that drives the mixing process and bounds the chaotic regions of the phase space.…

Plasma Physics · Physics 2016-10-05 David Ciro Taborda , Todd Edwin Evans , Iberê Luiz Caldas

We present a novel parametric finite element approach for simulating the surface diffusion of curves and surfaces. Our core strategy incorporates a predictor-corrector time-stepping method, which enhances the classical first-order temporal…

Numerical Analysis · Mathematics 2024-12-17 Wei Jiang , Chunmei Su , Ganghui Zhang , Lian Zhang

This paper reports investigations on the computation of material fronts in multi-fluid models using a Lagrange-Projection approach. Various forms of the Projection step are considered. Particular attention is paid to minimization of…

Numerical Analysis · Mathematics 2010-12-22 Christophe Chalons , Frédéric Coquel

Recently developed reduced-order modeling techniques aim to approximate nonlinear dynamical systems on low-dimensional manifolds learned from data. This is an effective approach for modeling dynamics in a post-transient regime where the…

Dynamical Systems · Mathematics 2023-09-27 Samuel E. Otto , Gregory R. Macchio , Clarence W. Rowley

We establish long-time existence for a projected Sobolev gradient flow of generalized integral Menger curvature in the Hilbert case, and provide $C^{1,1}$-bounds in time for the solution that only depend on the initial curve. The…

Classical Analysis and ODEs · Mathematics 2023-04-25 Jan Knappmann , Henrik Schumacher , Daniel Steenebrügge , Heiko von der Mosel

In this paper we analyse convergence of projected fixed-point iteration on a Riemannian manifold of matrices with fixed rank. As a retraction method we use `projector splitting scheme'. We prove that the projector splitting scheme converges…

Numerical Analysis · Mathematics 2016-04-08 Denis Kolesnikov , Ivan Oseledets

We introduce novel finite element schemes for curve diffusion and elastic flow in arbitrary codimension. The schemes are based on a variational form of a system that includes a specifically chosen tangential motion. We derive optimal $L^2$-…

Numerical Analysis · Mathematics 2025-09-29 Klaus Deckelnick , Robert Nürnberg

Space-Time Projection (STP) is introduced as a data-driven forecasting approach for high-dimensional and time-resolved data. The method computes extended space-time proper orthogonal modes from training data spanning a prediction horizon…

Machine Learning · Computer Science 2025-04-01 Oliver T. Schmidt

In this work, the projection-based embedded discrete fracture model (pEDFM) for corner-point grid (CPG) geometry is developed for simulation of flow and heat transfer in fractured porous media. Unlike classical embedded discrete fracture…

Computational Physics · Physics 2021-12-15 Mousa HosseiniMehr , Janio Piguave Tomala , Cornelis Vuik , Mohammed Al Kobaisi , Hadi Hajibeygi

We propose a sequential homotopy method for the solution of mathematical programming problems formulated in abstract Hilbert spaces under the Guignard constraint qualification. The method is equivalent to performing projected backward Euler…

Optimization and Control · Mathematics 2024-08-15 Andreas Potschka , Hans Georg Bock

We develop a stochastic model for Lagrangian velocity as it is observed in experimental and numerical fully developed turbulent flows. We define it as the unique statistically stationary solution of a causal dynamics, given by a stochastic…

This paper contains a phenomenological description of the whole U.S. forward rate curve (FRC), based on an data in the period 1990-1996. We find that the average FRC (measured from the spot rate) grows as the square-root of the maturity,…

Statistical Mechanics · Physics 2016-08-31 J. -P. Bouchaud , N. Sagna , R. Cont , N. El-Karoui , M. Potters

We introduce a new class of forward performance processes that are endogenous and predictable with regards to an underlying market information set and, furthermore, are updated at discrete times. We analyze in detail a binomial model whose…

Mathematical Finance · Quantitative Finance 2019-03-20 Bahman Angoshtari , Thaleia Zariphopoulou , Xun Yu Zhou

In this paper, we study the pricing of contracts in fixed income markets under volatility uncertainty in the sense of Knightian uncertainty or model uncertainty. The starting point is an arbitrage-free bond market under volatility…

Pricing of Securities · Quantitative Finance 2021-11-09 Julian Hölzermann

We introduce Random Projection Flows (RPFs), a principled framework for injective normalizing flows that leverages tools from random matrix theory and the geometry of random projections. RPFs employ random semi-orthogonal matrices, drawn…

Machine Learning · Computer Science 2025-11-26 Ahmad Ayaz Amin , Baha Uddin Kazi

We develop the theory of derived differential geometry in terms of bundles of curved $L_\infty[1]$-algebras, i.e. dg manifolds of positive amplitudes. We prove the category of derived manifolds is a category of fibrant objects. Therefore,…

Differential Geometry · Mathematics 2021-06-15 Kai Behrend , Hsuan-Yi Liao , Ping Xu

A new projection method based on radial basis functions (RBFs) is presented for discretizing the incompressible unsteady Stokes equations in irregular geometries. The novelty of the method comes from the application of a new technique for…

Numerical Analysis · Mathematics 2015-09-21 Edward J. Fuselier , Varun Shankar , Grady B. Wright

We present Functional Mean Flow (FMF) as a one-step generative model defined in infinite-dimensional Hilbert space. FMF extends the one-step Mean Flow framework to functional domains by providing a theoretical formulation for Functional…

Machine Learning · Computer Science 2025-11-18 Zhiqi Li , Yuchen Sun , Greg Turk , Bo Zhu
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