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Generalized additive models (GAMs) provide a way to blend parametric and non-parametric (function approximation) techniques together, making them flexible tools suitable for many modeling problems. For instance, GAMs can be used to…

Methodology · Statistics 2023-03-07 Antti Solonen , Stratos Staboulis

Granular materials are involved in most industrial and environmental processes, as well as many civil engineering applications. Although significant advances have been made in understanding the statics and dynamics of cohesionless grains…

Soft Condensed Matter · Physics 2025-11-21 Ram Sudhir Sharma , Alban Sauret

Coarse-graining or model reduction is a term describing a range of approaches used to extend the time-scale of molecular simulations by reducing the number of degrees of freedom. In the context of molecular simulation, standard…

Dynamical Systems · Mathematics 2023-11-14 Thomas Hudson , Xingjie Helen Li

Many current challenges involve understanding the complex dynamical interplay between the constituents of systems. Typically, the number of such constituents is high, but only limited data sources on them are available. Conventional…

Populations and Evolution · Quantitative Biology 2021-12-17 Jana C. Massing , Thilo Gross

Coarse-grained (CG) models are simplified representations of soft matter systems that are commonly employed to overcome size and time limitations in computational studies. Many approaches have been developed to construct and parametrise…

Statistical Mechanics · Physics 2022-09-27 Piero Luchi , Roberto Menichetti , Gianluca Lattanzi , Raffaello Potestio

Developing physics-based models for molecular simulation requires fitting many unknown parameters to diverse experimental datasets. Traditionally, this process is piecemeal and difficult to reproduce, leading to a fragmented landscape of…

Biological Physics · Physics 2025-04-10 Ryan K. Krueger , Megan C. Engel , Ryan Hausen , Michael P. Brenner

Computational models are quantitative representations of systems. By analyzing and comparing the outputs of such models, it is possible to gain a better understanding of the system itself. Though as the complexity of model outputs…

Machine Learning · Computer Science 2022-12-13 Colin G. Cess , Stacey D. Finley

We review some recent coarse-graining and multi-scale methods, but also put forward some new ideas for addressing such issues. We find that, if one is guided by nonequilibrium statistical mechanics and thermodynamics, it is possible to…

Soft Condensed Matter · Physics 2009-11-06 Patrick Ilg , Vlasis Mavrantzas , Hans Christian Öttinger

Coarse-grained models are a core computational tool in theoretical chemistry and biophysics. A judicious choice of a coarse-grained model can yield physical insight by isolating the essential degrees of freedom that dictate the…

Statistical Mechanics · Physics 2023-04-12 Shriram Chennakesavalu , David J. Toomer , Grant M. Rotskoff

Amphiphilic molecules spontaneously form self-assembled structures of various shapes depending on their molecular structures, the temperature, and other physical conditions. The functionalities of these structures are dictated by their…

Soft Condensed Matter · Physics 2024-04-18 Takeo Sudo , Satoki Ishiai , Yuuki Ishiwatari , Takahiro Yokoyama , Kenji Yasuoka , Noriyoshi Arai

The structure of polyelectrolytes is highly sensitive to small changes in the interactions between its monomers. In particular, interactions mediated by counterions play a significant role, and are affected by both specific molecular…

Soft Condensed Matter · Physics 2020-02-03 Pauline Bacle , Marie Jardat , Virginie Marry , Guillaume Mériguet , Guillaume Batôt , Vincent Dahirel

Our understanding of the physics of biological molecules, such as proteins and DNA, is limited because the approximations we usually apply to model inert materials are not in general applicable to soft, chemically inhomogeneous systems. The…

Quantum Physics · Physics 2010-07-13 Sarah Harris , Vivien M. Kendon

Probabilistic graphical models combine the graph theory and probability theory to give a multivariate statistical modeling. They provide a unified description of uncertainty using probability and complexity using the graphical model.…

Machine Learning · Statistics 2011-11-30 Yang Zhou

The molecular machinery of life is largely created via self-organisation of individual molecules into functional assemblies. Minimal coarse-grained models, where a whole macromolecule is represented by a small number of particles, can be of…

Biological Physics · Physics 2019-06-25 Anne E. Hafner , Johannes Krausser , Anđela Šarić

We present a universal approach to the investigation of the dynamics in generalized models. In these models the processes that are taken into account are not restricted to specific functional forms. Therefore a single generalized models can…

Chaotic Dynamics · Physics 2007-05-23 Thilo Gross , Ulrike Feudel

The generalized partially linear models on Riemannian manifolds are introduced. These models, like ordinary generalized linear models, are a generalization of partially linear models on Riemannian manifolds that allow for response variables…

Methodology · Statistics 2018-03-09 Amelia Simó , M. Victoria Ibáñez , Irene Epifanio , Vicent Gimeno

Bottom-up coarse-grained (CG) modeling expands the spatial and temporal scales of molecular simulation by seeking a reduced, thermodynamically consistent representation of an atomistic model. Developments in CG theory have largely focused…

Chemical Physics · Physics 2025-03-28 Patrick G. Sahrmann , Gregory A. Voth

Coarse-grained (CG) models can provide computationally efficient and conceptually simple characterizations of soft matter systems. While generic models probe the underlying physics governing an entire family of free-energy landscapes,…

Soft Condensed Matter · Physics 2019-08-15 Joseph F. Rudzinski

We present the state-of-the-art theoretical modeling, molecular simulation, and coarse-graining strategies for the transport of gases and liquids in nanoporous materials (pore size 1-100 nm). Special emphasis is placed on the transport of…

Soft Condensed Matter · Physics 2025-01-29 Alexander Schlaich , Jean-Louis Barrat , Benoit Coasne

Model biomembrane systems play a crucial role in advancing biomedical research by providing simplified yet effective platforms for exploring complex biological mechanisms. These systems span a wide range of scales, from…

Soft Condensed Matter · Physics 2025-10-01 Ajit Seth , Sajal K. Ghosh , Veerendra K. Sharma