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Large contingency tables summarizing categorical variables arise in many areas. For example in biology when a large number of biomarkers are cross-tabulated according to their discrete expression level. Interactions of the variables are…

Methodology · Statistics 2009-11-17 Corinne Dahinden , Markus Kalisch , Peter Bühlmann

Soft materials (e.g., enveloped viruses, liposomes, membranes and supercooled liquids) simultaneously deform or display collective behaviors, while undergoing atomic scale vibrations and collisions. While the multiple space-time character…

Soft Condensed Matter · Physics 2014-01-03 Peter Ortoleva , Abhishek Singharoy , Stephen Pankavich

Although coarse-grained models have been widely used to explain exotic phenomena in complex fluids, such as droplet formation in living cells, these conventional approaches often fail to capture the intricate microscopic degrees of freedom…

Soft Condensed Matter · Physics 2025-06-13 Masanari Shimada , Tetsuya J. Kobayashi

We consider an additive partially linear framework for modelling massive heterogeneous data. The major goal is to extract multiple common features simultaneously across all sub-populations while exploring heterogeneity of each…

Methodology · Statistics 2019-01-01 Binhuan Wang , Yixin Fang , Heng Lian , Hua Liang

In multiscale modelling, multiple models are used simultaneously to describe scale-dependent phenomena in a system of interest. Here we introduce a machine learning (ML)-based multiscale modelling framework for modelling hierarchical…

Geophysics · Physics 2022-04-13 Mark Ashworth , Ahmed Elsheikh , Florian Doster

Many important problems in the real world don't have unique solutions. It is thus important for machine learning models to be capable of proposing different plausible solutions with meaningful probability measures. In this work we introduce…

Machine Learning · Computer Science 2020-07-28 Di Qiu , Lok Ming Lui

When modeling longitudinal biomedical data, often dimensionality reduction as well as dynamic modeling in the resulting latent representation is needed. This can be achieved by artificial neural networks for dimension reduction, and…

Machine Learning · Statistics 2023-12-01 Göran Köber , Raffael Kalisch , Lara Puhlmann , Andrea Chmitorz , Anita Schick , Harald Binder

We propose an extension of the discretization approaches for multilayer shallow water models, aimed at making them more flexible and efficient for realistic applications to coastal flows. A novel discretization approach is proposed, in…

Numerical Analysis · Mathematics 2018-04-18 Luca Bonaventura , Enrique D. Fernández-Nieto , José Garres-Díaz , Gladys Narbona-Reina

We present initial results regarding the existence, stability and interaction of linear and nonlinear vibrational modes in a system of two coupled, one dimensional lattices with unequal numbers of masses. The effects on these nonlinear…

Biological Physics · Physics 2007-05-23 Kyle Forinash

Computational simulations have the potential to assist in liver resection surgeries by facilitating surgical planning, optimizing resection strategies, and predicting postoperative outcomes. The modeling of liver tissue across multiple…

Computational Engineering, Finance, and Science · Computer Science 2023-06-14 Adnan Ebrahem , Etienne Jessen , Marco F. P. ten Eikelder , Tarun Gangwar , Michał Mika , Dominik Schillinger

We develop an theoretical approach for predicting biodiversity in multi-dimensional niche spaces, arising due to ecological drivers such as competitive exclusion. The novelty of our approach relies on the fact that ecological niches are…

Populations and Evolution · Quantitative Biology 2015-06-11 Tommaso Biancalani , Lee DeVille , Nigel Goldenfeld

The goal of this paper is to provide mathematically rigorous tools for modelling the evolution of a community of interacting individuals. We model the population by a measure space where the measure determines the abundance of individual…

Probability · Mathematics 2017-05-17 Thomas Cass , Terry Lyons

Researchers develop models to explain the unknowns. These models typically involve parameters that capture tangible quantities, the estimation of which is desired. Parameter identifiability investigates the recoverability of the unknown…

Optimization and Control · Mathematics 2024-07-01 Anuththara Sarathchandra , Azadeh Aghaeeyan , Pouria Ramazi

The geometrical structure is among the most fundamental ingredients in understanding complex systems. Is there any systematic approach in defining structures quantitatively, rather than illustratively? If yes, what are the basic principles…

Fluid Dynamics · Physics 2020-05-27 Lipo Wang , Guiwen Tan , Hui Cao

We are interested in exploring interacting particle systems that can be seen as microscopic models for a particular structure of coupled transport flux arising when different populations are jointly evolving. The scenarios we have in mind…

Analysis of PDEs · Mathematics 2017-03-08 Manh Hong Duong , Adrian Muntean , Omar Richardson

Several problems in modeling and control of stochastically-driven dynamical systems can be cast as regularized semi-definite programs. We examine two such representative problems and show that they can be formulated in a similar manner. The…

Optimization and Control · Mathematics 2019-12-30 Armin Zare , Hesameddin Mohammadi , Neil K. Dhingra , Tryphon T. Georgiou , Mihailo R. Jovanović

Understanding how stochastic and non-linear deterministic processes interact is a major challenge in population dynamics theory. After a short review, we introduce a stochastic individual-centered particle model to describe the evolution in…

Probability · Mathematics 2009-06-29 Regis Ferriere , Viet Chi Tran

A pluri-Lagrangian (or Lagrangian multiform) structure is an attribute of integrability that has mainly been studied in the context of multidimensionally consistent lattice equations. It unifies multidimensional consistency with the…

Exactly Solvable and Integrable Systems · Physics 2019-02-22 Mats Vermeeren

The aim of the present paper is to efficiently describe the membrane potential dynamics of neural populations formed by species having a high density difference in specific brain areas. We propose a hybrid model whose main ingredients are a…

Neurons and Cognition · Quantitative Biology 2015-10-06 Anna Cattani , Sergio Solinas , Claudio Canuto

Multiscale models of materials, consisting of upscaling discrete simulations to continuum models, are unique in their capability to simulate complex materials behavior. The fundamental limitation in multiscale models is the presence of…

Computational Engineering, Finance, and Science · Computer Science 2020-12-22 Jingye Tan , Umberto Villa , Nima Shamsaei , Shuai Shao , Hussein M. Zbib , Danial Faghihi
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