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We show in this note how the machinery of C^1-approximate flows devised in the work "Flows driven by rough paths", and applied there to reprove and extend most of the results on Banach space-valued rough differential equations driven by a…

Probability · Mathematics 2013-09-25 Ismael Bailleul

This paper addresses enforcing non-vanishing constraints for solutions to a second order elliptic partial differential equation by appropriate choices of boundary conditions. We show that, in dimension $d\geq2$, under suitable regularity…

Analysis of PDEs · Mathematics 2019-05-09 Giovanni S. Alberti , Yves Capdeboscq

We establish sharp estimates for the convergence rate of the Kranosel'ski\v{\i}-Mann fixed point iteration in general normed spaces, and we use them to show that the asymptotic regularity bound recently proved in [11] (Israel Journal of…

Optimization and Control · Mathematics 2017-01-31 Mario Bravo , Roberto Cominetti

In this paper, we introduce an inertial version of the Proximal Incremental Aggregated Gradient method (PIAG) for minimizing the sum of smooth convex component functions and a possibly nonsmooth convex regularization function.…

Optimization and Control · Mathematics 2017-12-19 Xiaoya Zhang , Wei Peng , Hui Zhang , Wei Zhu

We prove a new smoothing type property for solutions of the 1d quintic Schr\"odinger equation. As a consequence, we prove that a family of natural gaussian measures are quasi-invariant under the flow of this equation. In the defocusing…

Analysis of PDEs · Mathematics 2021-08-23 F. Planchon , N. Tzvetkov , N. Visciglia

Bayesian nonparametric regression under a rescaled Gaussian process prior offers smoothness-adaptive function estimation with near minimax-optimal error rates. Hierarchical extensions of this approach, equipped with stochastic variable…

Statistics Theory · Mathematics 2020-12-15 Sheng Jiang , Surya T. Tokdar

We introduce an alternative closed form lower bound on the Gaussian process ($\mathcal{GP}$) likelihood based on the R\'enyi $\alpha$-divergence. This new lower bound can be viewed as a convex combination of the Nystr\"om approximation and…

Machine Learning · Statistics 2023-07-04 Xubo Yue , Raed Kontar

We show that, under mild assumptions on the limiting curve, a sequence of simple chordal planar curves converges uniformly whenever certain Loewner driving functions converge. We extend this result to random curves. The random version…

Probability · Mathematics 2012-04-05 Scott Sheffield , Nike Sun

We present a fast algorithm for global rigid symmetry detection with approximation guarantees. The algorithm is guaranteed to find the best approximate symmetry of a given shape, to within a user-specified threshold, with very high…

Computational Geometry · Computer Science 2016-09-20 Simon Korman , Roee Litman , Shai Avidan , Alex Bronstein

We show existence and uniqueness of solutions of stochastic path-dependent differential equations driven by cadlag martingale noise under joint local monotonicity and coercivity assumptions on the coefficients with a bound in terms of the…

Probability · Mathematics 2019-08-29 Sima Mehri , Michael Scheutzow

The article studies non-Gaussian extensions of a recently discovered link between certain Gaussian random fields, expressed as solutions to stochastic partial differential equations (SPDEs), and Gaussian Markov random fields. The focus is…

Methodology · Statistics 2012-06-15 David Bolin

We develop a general framework for pathwise stochastic integration that extends F\"ollmer's classical approach beyond gradient-type integrands and standard left-point Riemann sums and provides pathwise counterparts of It\^o, Stratonovich,…

Probability · Mathematics 2025-07-24 Purba Das , Anna P. Kwossek , David J. Prömel

This work establishes two versions of the Pontryagin-type maximum principles for partially observed optimal control of coupled forward stochastic partial differential equations (FSPDEs) and backward stochastic differential equations (BSDEs)…

Optimization and Control · Mathematics 2026-03-03 Hongjiang Qian , George Yin , Yanzhao Cao , Guannan Zhang

We consider the 1d nonlinear Schr\"odinger equation (NLS) on the torus with initial data distributed according to the Gaussian measure with covariance operator $(1 - \Delta)^{-s}$, where $\Delta$ is the Laplace operator. We prove that the…

Analysis of PDEs · Mathematics 2025-04-22 Alexis Knezevitch

In this article, we study the regularity theory for two linear equations that are important in fluid dynamics: the passive scalar equation for (time-varying) shear flows close to Couette in $\mathbb T \times [-1,1]$ with vanishing…

Analysis of PDEs · Mathematics 2024-05-30 Jacob Bedrossian , Siming He , Sameer Iyer , Fei Wang

Flow Matching has become a cornerstone of modern generative models like Stable Diffusion 3, largely due to the efficiency of its Rectified Flow (RF) variant. The success of RF hinges on iteratively learning straight trajectories, pushing…

Machine Learning · Computer Science 2026-05-19 Vansh Bansal , Saptarshi Roy , Purnamrita Sarkar , Alessandro Rinaldo

This paper studies the convergence rates of optimal transport (OT) map estimators, a topic of growing interest in statistics, machine learning, and various scientific fields. Despite recent advancements, existing results rely on regularity…

Statistics Theory · Mathematics 2024-12-12 Yizhe Ding , Runze Li , Lingzhou Xue

We perform a detailed study of the Yangian symmetry of smooth supersymmetric Maldacena-Wilson loops in planar N=4 super Yang-Mills theory. This hidden symmetry extends the global superconformal symmetry present for these observables. A…

High Energy Physics - Theory · Physics 2016-01-05 Niklas Beisert , Dennis Muller , Jan Plefka , Cristian Vergu

By carrying out refined curvature estimates, we prove better rigidity theorems of complete noncompact ancient solutions to the mean curvature flow in higher codimension under various Gauss image restriction.

Differential Geometry · Mathematics 2023-11-22 Hongbing Qiu , Y. L. Xin

We consider a broad class of semilinear SPDEs with multiplicative noise driven by a finite-dimensional Wiener process. We show that, provided that an infinite-dimensional analogue of H\"ormander's bracket condition holds, the Malliavin…

Probability · Mathematics 2019-11-11 Andris Gerasimovics , Martin Hairer