Data-driven methods to estimate the committor function in conceptual ocean models [PDF]
Nonlinear Processes in Geophysics, 2023 In recent years, several climate subsystems have been identified that may undergo a relatively rapid transition compared to the changes in their forcing.
V. Jacques-Dumas +5 more
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INFERRING OF REGULATORY NETWORKS FROM EXPRESSION DATA USING BAYESIAN NETWORKS [PDF]
Научно-технический вестник информационных технологий, механики и оптики, 2020 Subject of Research. The paper considers the inferring of gene regulatory networks in the form of Bayesian networks from gene expression data. We present this problem as the problem of the marginal probability estimation for each edge appearance in the ...
Alexander A. Loboda +1 more
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Rank-normalization, folding, and localization: An improved $\widehat{R}$ for assessing convergence of MCMC [PDF]
, 2020 Markov chain Monte Carlo is a key computational tool in Bayesian statistics, but it can be challenging to monitor the convergence of an iterative stochastic algorithm.
Bürkner, Paul-Christian +4 more
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Faster quantum mixing for slowly evolving sequences of Markov chains [PDF]
Quantum, 2018 Markov chain methods are remarkably successful in computational physics, machine learning, and combinatorial optimization. The cost of such methods often reduces to the mixing time, i.e., the time required to reach the steady state of the Markov chain ...
Davide Orsucci +2 more
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Robustness analysis of stochastic biochemical systems. [PDF]
PLoS ONE, 2014 We propose a new framework for rigorous robustness analysis of stochastic biochemical systems that is based on probabilistic model checking techniques. We adapt the general definition of robustness introduced by Kitano to the class of stochastic systems ...
Milan Ceska +3 more
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Neural dynamics as sampling: a model for stochastic computation in recurrent networks of spiking neurons. [PDF]
PLoS Computational Biology, 2011 The organization of computations in networks of spiking neurons in the brain is still largely unknown, in particular in view of the inherently stochastic features of their firing activity and the experimentally observed trial-to-trial variability of ...
Lars Buesing +3 more
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Simple, fast and accurate implementation of the diffusion approximation algorithm for stochastic ion channels with multiple states. [PDF]
PLoS ONE, 2012 BACKGROUND: The phenomena that emerge from the interaction of the stochastic opening and closing of ion channels (channel noise) with the non-linear neural dynamics are essential to our understanding of the operation of the nervous system.
Patricio Orio, Daniel Soudry
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COMPUTATIONAL LINGUISTICS AND ARTIFICIAL INTELLIGENCE [PDF]
Ziglôbitha: Computational linguistics, as an interdisciplinary field combining linguistics and computer science, aims to enable computers to process natural language.
Affas MAAMAR & Hadjer HADJCHERIF
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Fast parallelized sampling of Bayesian regression models for whole-genome prediction
Genetics Selection Evolution, 2020 Background Bayesian regression models are widely used in genomic prediction, where the effects of all markers are estimated simultaneously by combining the information from the phenotypic data with priors for the marker effects and other parameters such ...
Tianjing Zhao +3 more
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Using Bayesian inference to estimate plausible muscle forces in musculoskeletal models
Journal of NeuroEngineering and Rehabilitation, 2022 Background Musculoskeletal modeling is currently a preferred method for estimating the muscle forces that underlie observed movements. However, these estimates are sensitive to a variety of assumptions and uncertainties, which creates difficulty when ...
Russell T. Johnson +2 more
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