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相关论文: The quantization complexity of diffusion processes

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We present a Bayesian non-parametric way of inferring stochastic differential equations for both regression tasks and continuous-time dynamical modelling. The work has high emphasis on the stochastic part of the differential equation, also…

机器学习 · 统计学 2020-06-29 Martin Jørgensen , Marc Peter Deisenroth , Hugh Salimbeni

We consider the quantum complexity of computing Schatten $p$-norms and related quantities, and find that the problem of estimating these quantities is closely related to the one clean qubit model of computation. We show that the problem of…

量子物理 · 物理学 2017-06-29 Chris Cade , Ashley Montanaro

We consider the distributed source coding problem in which correlated data picked up by scattered sensors has to be encoded separately and transmitted to a common receiver, subject to a rate-distortion constraint. Although near-tooptimal…

信息论 · 计算机科学 2008-09-09 G. Maierbacher , J. Barros

We prove $L_p$ estimates of solutions to a conormal derivative problem for divergence form complex-valued higher-order elliptic systems on a half space and on a Reifenberg flat domain. The leading coefficients are assumed to be merely…

偏微分方程分析 · 数学 2012-03-08 Hongjie Dong , Doyoon Kim

We study approximation of embeddings between finite dimensional L_p spaces in the quantum model of computation. For the quantum query complexity of this problem matching (up to logarithmic factors) upper and lower bounds are obtained. The…

量子物理 · 物理学 2007-05-23 Stefan Heinrich

A multiscale method is proposed for a parabolic stochastic partial differential equation with additive noise and highly oscillatory diffusion. The framework is based on the localized orthogonal decomposition (LOD) method and computes a…

数值分析 · 数学 2023-04-28 Annika Lang , Per Ljung , Axel Målqvist

Diffusion models generate high-resolution images through iterative stochastic processes. In particular, the denoising method is one of the most popular approaches that predicts the noise in samples and denoises it at each time step. It has…

计算机视觉与模式识别 · 计算机科学 2024-01-22 Juno Hwang , Yong-Hyun Park , Junghyo Jo

In this note we study advection diffusion equations associated to incompressible $W^{1,p}$ velocity fields with $p>2$. We present new estimates on the energy dissipation rate and we discuss applications to the study of upper bounds on the…

偏微分方程分析 · 数学 2021-03-17 Elia Bruè , Quoc-Hung Nguyen

Complex systems are composed of many particles or agents that move and interact with one another. The underlying mathematical framework to model many of these systems must incorporate the spatial transport of particles and their…

统计力学 · 物理学 2026-02-09 Mauricio J. del Razo , Tommaso Lamma , Wout Merbis

This article is dedicated to unifying the framework used to derive the Wiener--Hopf equations arising from some discrete and continuous wave diffraction problems.The main tools are the discrete Green's identity and the appropriate notion of…

数学物理 · 物理学 2025-07-08 A. I. Korolkov , R. C. Assier , A. V. Kisil

Due to the high complexity and technical requirements of industrial production processes, surface defects will inevitably appear, which seriously affects the quality of products. Although existing lightweight detection networks are highly…

计算机视觉与模式识别 · 计算机科学 2024-08-27 Xuyi Yu

Advances in microscopy imaging enable researchers to visualize structures at the nanoscale level thereby unraveling intricate details of biological organization. However, challenges such as image noise, photobleaching of fluorophores, and…

图像与视频处理 · 电气工程与系统科学 2024-09-19 Pamela Osuna-Vargas , Maren H. Wehrheim , Lucas Zinz , Johanna Rahm , Ashwin Balakrishnan , Alexandra Kaminer , Mike Heilemann , Matthias Kaschube

We develop unified and easy to use framework to study robust fully discrete numerical methods for nonlinear degenerate diffusion equations $$ \partial_t u-\mathfrak{L}[\varphi(u)]=f(x,t) \qquad\text{in}\qquad \mathbb{R}^N\times(0,T), $$…

数值分析 · 数学 2018-10-17 Félix del Teso , Jørgen Endal , Espen R. Jakobsen

Increasingly larger data sets of processes in space and time ask for statistical models and methods that can cope with such data. We show that the solution of a stochastic advection-diffusion partial differential equation provides a…

统计方法学 · 统计学 2016-02-18 Fabio Sigrist , Hans R. Künsch , Werner A. Stahel

The $L^p$ maximal inequalities for martingales are one of the classical results in the theory of stochastic processes. Here we establish the sharp moderate maximal inequalities for one-dimensional diffusion processes, which include the…

概率论 · 数学 2021-11-05 Xian Chen , Yong Chen , Mumien Cheng , Chen Jia

The aim of this paper is to understand the influence of a dissipative term which is small in the sense that it is asymptotically below scaling on the asymptotic properties of solutions. A diagonalization procedure is applied in order to…

偏微分方程分析 · 数学 2007-05-23 Jens Wirth

We derive a high-resolution formula for the quantization problem under Orlicz norm distortion. In this setting, the optimal point density solves a variational problem which comprises a function $g:\mathbb{R}_+\to[0,\infty)$ characterizing…

概率论 · 数学 2010-10-21 Steffen Dereich , Christian Vormoor

Quantum state discrimination is an important problem in many information processing tasks. In this work we are concerned with finding its best possible sample complexity when the states are preprocessed by a quantum channel that is required…

量子物理 · 物理学 2024-06-28 Hao-Chung Cheng , Christoph Hirche , Cambyse Rouzé

We improve the time decay estimates of solutions to the one-dimensional fractional diffusion equation involving the Caputo derivative. The equation is considered on the half-line. Depending on the boundary condition, we show that solutions…

偏微分方程分析 · 数学 2025-11-11 Barbara Łupińska , Piotr Rybka

We present a new and relatively elementary method for studying the solution of the initial-value problem for dispersive linear and integrable equations in the large-$t$ limit, based on a generalization of steepest descent techniques for…

偏微分方程分析 · 数学 2018-09-06 Momar Dieng , Kenneth D. T. -R. McLaughlin , Peter D. Miller
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