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In this paper, we propose a deep evolutionary learning (DEL) process that integrates fragment-based deep generative model and multi-objective evolutionary computation for molecular design. Our approach enables (1) evolutionary operations in…

Neural and Evolutionary Computing · Computer Science 2021-02-02 Yifeng Li , Hsu Kiang Ooi , Alain Tchagang

Equations governing physico-chemical processes are usually known at microscopic spatial scales, yet one suspects that there exist equations, e.g. in the form of Partial Differential Equations (PDEs), that can explain the system evolution at…

Machine Learning · Statistics 2021-03-31 Hassan Arbabi , Ioannis Kevrekidis

This work proposes a novel method for semi-supervised learning from partially labeled massive network-structured datasets, i.e., big data over networks. We model the underlying hypothesis, which relates data points to labels, as a graph…

Machine Learning · Computer Science 2017-05-16 Alexander Jung , Alfred O. Hero , Alexandru Mara , Saeed Jahromi

This paper proposes a mathematical model for replicating a simple dynamics in an aquarium with two components; bacteria and organic matter. The model is based on a system of partial differential equations (PDEs) with four components: the…

Analysis of PDEs · Mathematics 2024-01-23 Ken Furukawa , Hiroyuki Kitahata

We consider compartmental models in epidemiology. For the study of the divergence of the stochastic model from its corresponding deterministic limit (i.e., the solution of an ODE) for long time horizon, a large deviations principle suggests…

Probability · Mathematics 2015-01-16 Peter Kratz , Etienne Pardoux , Brice Samegni Kepgnou

Variation in a sample of molecular sequence data informs about the past evolutionary history of the sample's population. Traditionally, Bayesian modeling coupled with the standard coalescent, is used to infer the sample's bifurcating…

Applications · Statistics 2024-10-22 Julie Zhang , Julia A. Palacios

Transportation processes, which play a prominent role in the life and social sciences, are typically described by discrete models on lattices. For studying their dynamics a continuous formulation of the problem via partial differential…

Symbolic Computation · Computer Science 2016-03-22 Christoph Koutschan , Helene Ranetbauer , Georg Regensburger , Marie-Therese Wolfram

In recent years, numerous advances have been made in understanding how epidemic dynamics is affected by changes in individual behaviours. We propose an SIS-based compartmental model to tackle the simultaneous and coupled evolution of an…

Physics and Society · Physics 2025-11-04 Giulia de Meijere , Hugo Martin

Recent progress in scientific machine learning (SciML) has opened up the possibility of training novel neural network architectures that solve complex partial differential equations (PDEs). Several (nearly data free) approaches have been…

We present a multiscale approach to model diffusion in a crowded environment and its effect on the reaction rates. Diffusion in biological systems is often modeled by a discrete space jump process in order to capture the inherent noise of…

Subcellular Processes · Quantitative Biology 2016-03-18 Lina Meinecke

In this paper we analyse a class of nonlinear cross-diffusion systems for two species with local repulsive interactions that exhibit a formal gradient flow structure with respect to the Wasserstein metric. We show that systems where the…

Analysis of PDEs · Mathematics 2019-06-11 M. Burger , J. A. Carrillo , J. -F. Pietschmann , M. Schmidtchen

Graph coloring is a challenging combinatorial optimization problem with a wide range of applications. In this paper, a distribution evolutionary algorithm based on a population of probability model (DEA-PPM) is developed to address it…

Neural and Evolutionary Computing · Computer Science 2023-05-03 Yongjian Xu , Huabin Cheng , Ning Xu , Yu Chen , Chengwang Xie

Discrete probability laws underpin statistical modeling, yet the catalog of interpretable distributions has expanded only gradually through centuries of case-by-case mathematical derivations. We introduce symbolic density estimation (SDE),…

Machine Learning · Computer Science 2026-05-25 Ziwen Liu , Meng Li

We propose a computational approach to modeling the collective dynamics of populations of coupled heterogeneous biological oscillators. In contrast to Monte Carlo simulation, this approach utilizes generalized Polynomial Chaos (gPC) to…

Quantitative Methods · Quantitative Biology 2007-05-23 Katherine A. Bold , Yu Zou , Ioannis G. Kevrekidis , Michael A. Henson

Many imaging techniques for biological systems -- like fixation of cells coupled with fluorescence microscopy -- provide sharp spatial resolution in reporting locations of individuals at a single moment in time but also destroy the dynamics…

Subcellular Processes · Quantitative Biology 2024-05-15 Christopher E. Miles , Scott A. McKinley , Fangyuan Ding , Richard B. Lehoucq

Many animal groups are heterogeneous and may even consist of individuals of different species, called mixed-species flocks. Mathematical and computational models of collective animal movement behaviour, however, typically assume that groups…

Adaptation and Self-Organizing Systems · Physics 2019-03-27 Gokul G. Nair , Athmanathan Senthilnathan , Srikanth K. Iyer , Vishwesha Guttal

We present a flexible branching process model for cell population dynamics in synchrony/time-series experiments used to study important cellular processes. Its formulation is constructive, based on an accounting of the unique cohorts in the…

Applications · Statistics 2010-09-30 David A. Orlando , Edwin S. Iversen , Alexander J. Hartemink , Steven B. Haase

Asymmetric damage segregation (ADS) is ubiquitous among unicellular organisms: After a mother cell divides, its two daughter cells receive sometimes slightly, sometimes strongly different fractions of damaged proteins accumulated in the…

Populations and Evolution · Quantitative Biology 2023-02-17 Arkady Pikovsky , Lev S. Tsimring

Phylogenetic networks extend phylogenetic trees to allow for modeling reticulate evolutionary processes such as hybridization. They take the shape of a rooted, directed, acyclic graph, and when parameterized with evolutionary parameters,…

Populations and Evolution · Quantitative Biology 2018-08-28 R. A. L. Elworth , H. A. Ogilvie , J. Zhu , L. Nakhleh

We derive the full kinetic equations describing the evolution of the probability density distribution for a structured population such as cells distributed according to their ages and sizes. The kinetic equations for such a "sizer-timer"…

Populations and Evolution · Quantitative Biology 2026-05-12 Mingtao Xia , Tom Chou