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This paper introduces a variational formulation of natural selection, paying special attention to the nature of "things" and the way that different "kinds" of "things" are individuated from - and influence - each other. We use the Bayesian…

Populations and Evolution · Quantitative Biology 2023-07-05 Karl Friston , Daniel Ari Friedman , Axel Constant , V. Bleu Knight , Thomas Parr , John O. Campbell

Isothermal-isobaric molecular dynamics simulations are used to examine the microscopic structure and some properties of water-methanol liquid mixture. The TIP4P/2005 and SPC/E water models are combined with the united atom TraPPE and the…

Soft Condensed Matter · Physics 2019-03-28 M. Cruz Sanchez , H. Dominguez , O. Pizio

We develop a statistical toolbox for a quantitative model evaluation of stochastic reaction-diffusion systems modeling space-time evolution of biophysical quantities on the intracellular level. Starting from space-time data $X_N(t,x)$, as,…

Methodology · Statistics 2023-07-14 Gregor Pasemann , Carsten Beta , Wilhelm Stannat

Parameter inference and uncertainty quantification are important steps when relating mathematical models to real-world observations, and when estimating uncertainty in model predictions. However, methods for doing this can be…

Quantitative Methods · Quantitative Biology 2025-08-27 Michael J. Plank , Matthew J. Simpson

Machine learning (ML) and deep learning models are extensively used for parameter optimization and regression problems. However, not all inverse problems in ML are ``identifiable,'' indicating that model parameters may not be uniquely…

Machine Learning · Computer Science 2023-07-24 Reza Sameni

A new upscaling procedure that provides 1D representations of 2D mixing-limited reactive transport systems is developed and applied. A key complication with upscaled models in this setting is that the procedure must differentiate between…

Fluid Dynamics · Physics 2022-10-05 Ricardo H. Deucher , Louis J. Durlofsky

Individuals may differ in their parameter values. This article discusses a three-step method of studying such differences by calculating and then modeling "individual parameter contributions", making the study of heterogeneity in arbitrary…

Methodology · Statistics 2013-04-15 Daniel Leonard Oberski

Collecting labeled data for many important tasks in chemoinformatics is time consuming and requires expensive experiments. In recent years, machine learning has been used to learn rich representations of molecules using large scale…

Machine Learning · Computer Science 2022-05-20 A. Tevosyan , L. Khondkaryan , H. Khachatrian , G. Tadevosyan , L. Apresyan , N. Babayan , H. Stopper , Z. Navoyan

Coarse-grained modeling in molecular simulations serves not only to extend accessible time and length scales beyond atomistic limits, but also to reduce high-dimensional chemical data to low-dimensional representations that expose the…

Chemical Physics · Physics 2026-05-19 Michael N. Sakano , Alejandro Strachan

Leptonic one-zone radiation models are commonly used to describe multi-wavelength data and explore the physical properties of high-energy sources, such as active galactic nuclei. However, these models often require a large number of free…

High Energy Astrophysical Phenomena · Physics 2025-10-22 F. Apel , A. Omeliukh , A. Franckowiak , J. Lederer

Infrequent Metadynamics is a popular method to obtain the rates of long timescale processes from accelerated simulations. The inference procedure is based on rescaling the first-passage times of Metadynamics trajectories using a…

Chemical Physics · Physics 2025-03-04 Ofir Blumer , Shlomi Reuveni , Barak Hirshberg

We have investigated thermodynamic and dynamic properties as well as the dielectric constant of water-metha\-nol model mixtures in the entire range of composition by using constant pressure molecular dynamics simulations at ambient…

Soft Condensed Matter · Physics 2015-12-25 E. Galicia-Andrés , H. Dominguez , L. Pusztai , O. Pizio

In biomedical studies, we are often interested in the association between different types of covariates and the times to disease events. Because the relationship between the covariates and event times is often complex, standard survival…

Methodology · Statistics 2024-01-19 Hoi Min Ng , Kin Yau Wong

The potential positive impact of autonomous driving and driver assistance technolo- gies have been a major impetus over the last decade. On the flip side, it has been a challenging problem to analyze the performance of human drivers or…

Machine Learning · Computer Science 2018-04-27 Dicong Qiu , Karthik Paga

Biophysical models describing complex, cellular phenomena typically include systems of nonlinear differential equations with many free parameters. While experimental measurements can fix some parameters, those describing internal cellular…

Computational Physics · Physics 2025-07-08 Joseph M. Marcinik , Martín A. Toderi , Dolores Bozovic

Estimating conditional average dose responses (CADR) is an important but challenging problem. Estimators must correctly model the potentially complex relationships between covariates, interventions, doses, and outcomes. In recent years, the…

Machine Learning · Computer Science 2024-06-13 Christopher Bockel-Rickermann , Toon Vanderschueren , Tim Verdonck , Wouter Verbeke

Autonomous vehicles currently suffer from a time-inefficient driving style caused by uncertainty about human behavior in traffic interactions. Accurate and reliable prediction models enabling more efficient trajectory planning could make…

Robotics · Computer Science 2023-02-21 Julian Frederik Schumann , Jens Kober , Arkady Zgonnikov

In standardized educational testing, test items are reused in multiple test administrations. To ensure the validity of test scores, the psychometric properties of items should remain unchanged over time. In this paper, we consider the…

Applications · Statistics 2021-10-26 Yunxiao Chen , Yi-Hsuan Lee , Xiaoou Li

Autonomous racing is a challenging problem, as the vehicle needs to operate at the friction or handling limits in order to achieve minimum lap times. Autonomous race cars require highly accurate perception, state estimation, planning and…

Robotics · Computer Science 2023-03-16 Dvij Kalaria , Qin Lin , John M. Dolan

The hydrodynamics of the dense confining fuel shell is of great importance in defining the behaviour of the burning plasma and burn propagation regimes of inertial confinement fusion experiments. However, it is difficult to probe due to its…