This article reviews the concepts and methods of variational path sampling. These methods allow computational studies of rare events in systems driven arbitrarily far from equilibrium. Based upon a statistical mechanics of trajectory space and leveraging the theory of large deviations, they provide a perspective from which dynamical phenomena can be studied with the same types of ensemble reweighting ideas that have been used for static equilibrium properties. Applications to chemical, material, and biophysical systems are highlighted.
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http://dx.doi.org/10.1146/annurev-physchem-083122-115001 | DOI Listing |
Annu Rev Phys Chem
February 2025
1Department of Chemistry, University of California, Berkeley, California, USA;
This article reviews the concepts and methods of variational path sampling. These methods allow computational studies of rare events in systems driven arbitrarily far from equilibrium. Based upon a statistical mechanics of trajectory space and leveraging the theory of large deviations, they provide a perspective from which dynamical phenomena can be studied with the same types of ensemble reweighting ideas that have been used for static equilibrium properties.
View Article and Find Full Text PDFPLoS One
February 2025
Institute of Engineering and Technology, Hubei University of Science and Technology, Xianning, China.
The "Internet of Body" is an emerging technology that is centered on the human body and connected to the Internet. It can monitor a variety of human data (such as heart rate, blood oxygen content, etc.) and communicate with digital pills, wearable devices, etc.
View Article and Find Full Text PDFPLoS Comput Biol
January 2025
Department of Biomedical Informatics, University of Colorado Anschutz School of Medicine, Aurora, Colorado, United States of America.
While single-cell experiments provide deep cellular resolution within a single sample, some single-cell experiments are inherently more challenging than bulk experiments due to dissociation difficulties, cost, or limited tissue availability. This creates a situation where we have deep cellular profiles of one sample or condition, and bulk profiles across multiple samples and conditions. To bridge this gap, we propose BuDDI (BUlk Deconvolution with Domain Invariance).
View Article and Find Full Text PDFEntropy (Basel)
December 2024
Shandong Artificial Intelligence Institute, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250014, China.
Image segmentation is a crucial task in artificial intelligence fields such as computer vision and medical imaging. While convolutional neural networks (CNNs) have achieved notable success by learning representative features from large datasets, they often lack geometric priors and global object information, limiting their accuracy in complex scenarios. Variational methods like active contours provide geometric priors and theoretical interpretability but require manual initialization and are sensitive to hyper-parameters.
View Article and Find Full Text PDFRev Sci Instrum
November 2024
Yunnan Key Laboratory of Computer Technology Applications, Kunming University of Science and Technology, Kunming 650500, China.
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