Results 11 to 20 of about 1,820,384 (367)
Procedia Computer Science, 2015 Dropout has recently emerged as a powerful and simple method for training neural networks preventing co-adaptation by stochastically omitting neurons.
Herlau, Tue +2 more
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Neural Computation, 1992 Although Bayesian analysis has been in use since Laplace, the Bayesian method of model-comparison has only recently been developed in depth. In this paper, the Bayesian approach to regularization and model-comparison is demonstrated by studying the ...
MacKay, David J. C.
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Journal of Risk and Financial Management, 2020 Since the advent of Markov chain Monte Carlo (MCMC) methods in the early 1990s, Bayesian methods have been proposed for a large and growing number of applications. One of the main advantages of Bayesian inference is the ability to deal with many different sources of uncertainty, including data, models, parameters and parameter restriction uncertainties,
Bernardi Mauro +2 more
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Pertinence of Predictive Models as Regards the Behavior of Observed Biological and Artificial Phenomena [PDF]
Athens Journal of Health and Medical Sciences, 2021 In this assessment, we have made an effort of synthesis on the role of theoretical and observational investigations in the analysis of the concepts and functioning of different natural biological and artificial phenomena.
Adel Razek
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Bayesian correction for covariate measurement error: a frequentist evaluation and comparison with regression calibration [PDF]
, 2016 Bayesian approaches for handling covariate measurement error are well established, and yet arguably are still relatively little used by researchers. For some this is likely due to unfamiliarity or disagreement with the Bayesian inferential paradigm.
Bartlett, Jonathan W., Keogh, Ruth H.
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Uncertainty of feedback and state estimation determines the speed of motor adaptation
Frontiers in Computational Neuroscience, 2010 Humans can adapt their motor behaviors to deal with ongoing changes. To achieve this, the nervous system needs to estimate central variables for our movement based on past knowledge and new feedback, both of which are uncertain. In the Bayesian framework,
Kunlin Wei +4 more
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Epigenetics, 2021 Epigenetic architecture is influenced by genetic and environmental factors, but little is known about their relative contributions or longitudinal dynamics.
Chris McKennan +14 more
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Inference of fuzzy reliability model for inverse Rayleigh distribution
AIMS Mathematics, 2021 In this paper, the question of inference of the reliability parameter of fuzzy stress strength ${R_F} = P(Y < X)$ is attached to the difference between stress and strength values when X and Y are independently distributed from inverse Rayleigh random ...
Mohamed A. H. Sabry +5 more
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A Bayesian approach to constrained single- and multi-objective optimization [PDF]
, 2016 This article addresses the problem of derivative-free (single- or multi-objective) optimization subject to multiple inequality constraints. Both the objective and constraint functions are assumed to be smooth, non-linear and expensive to evaluate.
A Bayesian +7 more
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SSRN Electronic Journal, 2011 Chapter written for the Handbook of Research Methods and Applications on Empirical Macroeconomics, edited by Nigar Hashimzade and Michael Thornton, forth- coming in 2012 (Edward Elgar Publishing). This chapter presents an introductory review of Bayesian methods for research in empirical macroeconomics.
Bauwens, L, Korobilis, D
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