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Mixed effects (ME) models inform a vast array of problems in the physical and social sciences, and are pervasive in meta-analysis. We consider ME models where the random effects component is linear. We then develop an efficient approach for…

Exploring the free-energy landscape along reaction coordinates or system parameters $\lambda$ is central to many studies of high-dimensional model systems in physics, e.g. large molecules or spin glasses. In simulations this usually…

Statistical Mechanics · Physics 2018-09-05 Viveca Lindahl , Jack Lidmar , Berk Hess

For decades, it was unknown how electron bifurcating systems in Nature prevented energy-wasting short-circuiting reactions that have large driving forces, so synthetic electron bifurcating molecular machines could not be designed and built.…

Biological Physics · Physics 2020-09-09 Jonathon L. Yuly , Peng Zhang , Carolyn E. Lubner , John W. Peters , David N. Beratan

In this paper, we address the performance degradation of efficient diffusion models by introducing Multi-architecturE Multi-Expert diffusion models (MEME). We identify the need for tailored operations at different time-steps in diffusion…

Computer Vision and Pattern Recognition · Computer Science 2023-12-29 Yunsung Lee , Jin-Young Kim , Hyojun Go , Myeongho Jeong , Shinhyeok Oh , Seungtaek Choi

Electromigration (EM) is one of the major concerns in the reliability analysis of very large scale integration (VLSI) systems due to the continuous technology scaling. Accurately predicting the time-to-failure of integrated circuits (IC)…

Machine Learning · Computer Science 2022-05-19 Tianshu Hou , Peining Zhen , Ngai Wong , Quan Chen , Guoyong Shi , Shuqi Wang , Hai-Bao Chen

Free-energy differences between pairs of end-states can be estimated based on molecular dynamics (MD) simulations using standard pathway-dependent methods such as thermodynamic integration (TI), free-energy perturbation, or Bennett's…

In this PhD thesis, we explore and apply methods inspired by the free energy principle to two important areas in machine learning and neuroscience. The free energy principle is a general mathematical theory of the necessary…

Artificial Intelligence · Computer Science 2021-08-31 Beren Millidge

Linear Mixed-Effects (LME) models are a fundamental tool for modeling correlated data, including cohort studies, longitudinal data analysis, and meta-analysis. Design and analysis of variable selection methods for LMEs is more difficult…

We perform an extrapolative analysis of "fast-growth" free-energy-difference (DF) estimates of a computer-modeled, fully-solvated ethane<->methanol transformation. The results suggest that extrapolation can greatly reduce the systematic…

Chemical Physics · Physics 2007-05-23 Daniel M. Zuckerman , Thomas B. Woolf

Resampling algorithms are a useful approach to deal with imbalanced learning in multilabel scenarios. These methods have to deal with singularities in the multilabel data, such as the occurrence of frequent and infrequent labels in the same…

Machine Learning · Computer Science 2025-01-22 Antonio J. Rivera , Miguel A. Dávila , David Elizondo , María J. del Jesus , Francisco Charte

This paper proposes a methodology to estimate stress in the subsurface by a hybrid method combining finite element modeling and neural networks. This methodology exploits the idea of obtaining a multi-frequency solution in the numerical…

Machine Learning · Computer Science 2020-08-27 Xavier Garcia , Adrian Rodriguez-Herrera

Nonequilibrium, ``fast switching'' estimates of equilibrium free energy differences, Delta F, are often plagued by poor convergence due to dissipation. We propose a method to improve these estimates by generating trajectories with reduced…

Statistical Mechanics · Physics 2009-11-13 Suriyanarayanan Vaikuntanathan , Christopher Jarzynski

Rearranging the six-dimensional phase space of particles in plasma can release energy. The rearrangement may happen through the application of electric and magnetic fields, subject to various constraints. The maximum energy that can be…

Plasma Physics · Physics 2020-07-15 E. J. Kolmes , P. Helander , N. J. Fisch

Mixed-effects regression models represent a useful subclass of regression models for grouped data; the introduction of random effects allows for the correlation between observations within each group to be conveniently captured when…

Methodology · Statistics 2024-09-25 Jackson Zhou , John T. Ormerod , Clara Grazian

Electronic stopping (ES) of energetic atoms is not taken care of by the interatomic potentials used in molecular dynamics (MD) simulations when simulating collision cascades. The Lindhard-Scharff (LS) formula for electronic stopping is…

Computational Physics · Physics 2020-10-06 H. Hemani , A. Majalee , U. Bhardwaj , A. Arya , K. Nordlund , M. Warrier

We study the problem of finding efficient sampling policies in an edge-based feedback system, where sensor samples are offloaded to a back-end server that processes them and generates feedback to a user. Sampling the system at maximum…

Information Theory · Computer Science 2023-02-07 Vishnu Narayanan Moothedath , Jaya Prakash Champati , James Gross

An important goal of environmental health research is to assess the health risks posed by mixtures of multiple environmental exposures. In these mixtures analyses, flexible models like Bayesian kernel machine regression and multiple index…

Methodology · Statistics 2025-12-29 Glen McGee , Joseph Antonelli

The relative energies of different phases or polymorphs of molecular solids can be small, less than a kiloJoule/mol. Reliable description of such energy differences requires high quality treatment of electron correlations, typically beyond…

Chemical Physics · Physics 2024-02-19 Khanh Ngoc Pham , Marcin Modrzejewski , Jiří Klimeš

A simple method to reduce the numerical cost in free electron laser (FEL) simulations is presented, which is based on retrieving a spatially-coherent component of microbunching to suppress artifact effects that can potentially overestimate…

Accelerator Physics · Physics 2023-11-01 Takashi Tanaka

There have been a lot of methods aimed at studying the limiting free energy per particle (LFEPP) for 3-dimensional (3D) Ising model in absence of an external magnetic field. These methods are elegant, but most of them are complicated and…

Statistical Mechanics · Physics 2025-01-06 Rong Qiang Wei