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Coarse-graining techniques play a central role in reducing the complexity of stochastic models, and are typically characterised by a mapping which projects the full state of the system onto a smaller set of variables which captures the…

Probability · Mathematics 2023-09-28 Bastian Hilder , Upanshu Sharma

Image-based crop growth modeling can substantially contribute to precision agriculture by revealing spatial crop development over time, which allows an early and location-specific estimation of relevant future plant traits, such as leaf…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Lukas Drees , Dereje T. Demie , Madhuri R. Paul , Johannes Leonhardt , Sabine J. Seidel , Thomas F. Döring , Ribana Roscher

We present a new framework for coarse-graining molecular dynamics models for crystalline solids. The reduction method is based on a Galerkin projection to a subspace, whose dimension is much smaller than that of the full atomistic model.…

Numerical Analysis · Mathematics 2012-10-17 Xiantao Li

A model of a discrete pregeometry on a microscopic scale is introduced. This model is a finite network of finite elementary processes. The mathematical description is a d-graph that is a generalization of a graph. This is the particular…

General Relativity and Quantum Cosmology · Physics 2010-04-29 Alexey L. Krugly

We introduce Coarse-Grained Nonlinear Dynamics, an efficient and universal parameterization of nonlinear system dynamics based on the Volterra series expansion. These models require a number of parameters only quasilinear in the system's…

Signal Processing · Electrical Eng. & Systems 2020-10-15 Span Spanbauer , Ian Hunter

Quantifying organism-level phenotypes, such as growth dynamics and biomass accumulation, is fundamental to understanding agronomic traits and optimizing crop production. However, quality growing data of plants at scale is difficult to…

Quantitative Methods · Quantitative Biology 2025-07-10 Adam J Riesselman , Evan M Cofer , Therese LaRue , Wim Meeussen

We study the effect of high-order statistics of data on the learning dynamics of neural networks (NNs) by using a moment-controllable non-Gaussian data model. Considering the expressivity of two-layer neural networks, we first construct the…

Machine Learning · Statistics 2026-02-03 Onat Ure , Samet Demir , Zafer Dogan

We introduce a generalized machine learning framework to probabilistically parameterize upper-scale models in the form of nonlinear PDEs consistent with a continuum theory, based on coarse-grained atomistic simulation data of mechanical…

In this study, we introduce novel methodologies designed to adapt original data in response to the dynamics of persistence diagrams along Wasserstein gradient flows. Our research focuses on the development of algorithms that translate…

Algebraic Topology · Mathematics 2024-12-06 Minghua Wang , Jinhui Xu

Coarse-grained (CG) molecular dynamics (MD) simulations can simulate large molecular complexes over extended timescales by reducing degrees of freedom. A critical step in CG modeling is the selection of the CG mapping algorithm, which…

Soft Condensed Matter · Physics 2025-07-23 Soumya Mondal , Subhanu Halder , Debarchan Basu , Sandeep Kumar , Tarak Karmakar

These lecture notes introduce the statistical analysis of continuous-time generative models built from Markov dynamics. We begin with the stochastic-calculus foundations of score-based diffusion models, including time reversal, score…

Statistics Theory · Mathematics 2026-04-27 Eddie Aamari , Arthur Stéphanovitch

Most methods for modelling dynamics posit just two time scales: a fast and a slow scale. But many applications, including many in continuum mechanics, possess a wide variety of space-time scales; often they possess a continuum of space-time…

Cellular Automata and Lattice Gases · Physics 2008-02-11 A. J. Roberts

In this paper, we present a continuum model for the dynamics of low angle grain boundaries in two dimensions based on the motion of constituent dislocations of the grain boundaries. The continuum model consists of an equation for the motion…

Materials Science · Physics 2018-06-13 Luchan Zhang , Yang Xiang

With the present paper we conclude the presentation of a semianalytical model of hierarchical clustering of bound virialized objects formed by gravitational instability from a random Gaussian field of density fluctuations. In paper I, we…

Astrophysics · Physics 2009-10-28 Alberto Manrique , Eduard Salvador-Sole

We present a general model for the growth of weighted networks in which the structural growth is coupled with the edges' weight dynamical evolution. The model is based on a simple weight-driven dynamics and a weights' reinforcement…

Statistical Mechanics · Physics 2009-11-10 Alain Barrat , Marc Barthelemy , Alessandro Vespignani

Coupled length and time scales determine the dynamic behavior of polymers and underlie their unique viscoelastic properties. To resolve the long-time dynamics it is imperative to determine which time and length scales must be correctly…

Soft Condensed Matter · Physics 2016-02-16 K. Michael Salerno , Anupriya Agrawal , Dvora Perahia , Gary S. Grest

Understanding and controlling the properties and dynamics of topological defects is a lasting challenge in the study of two-dimensional materials, and is crucial to achieve high-quality films required for technological applications. Here…

Materials Science · Physics 2017-06-28 Doaa Taha , S. K. Mkhonta , K. R. Elder , Zhi-Feng Huang

Discrete and continuous models belonging to a universality class share the same linearities and (or) nonlinearities. In this work, we propose a new approach to calculate coarse grained coefficients of the continuous differential equation…

Statistical Mechanics · Physics 2012-11-22 R. C. Buceta , D. Hansmann

We investigate the existence and first percolation properties of general stopped germ-grain models. They are defined via a random set of germs generated by a homogeneous planar Poisson point process in $\mathbf{R}^{2}$. From each germ, a…

Probability · Mathematics 2020-12-08 David Coupier , David Dereudre , Simon Le Stum

During grain growth in multiphase system, a convincing understanding on how the evolution kinetics of an individual phase-grains relates to the growth rate of entire microstructure is yet to be achieved. Therefore, in this work, comfortably…

Materials Science · Physics 2021-08-06 P G Kubendran Amos , Ramanathan Perumal , Arnd Koeppe , Britta Nestler