Results 31 to 40 of about 514,307 (282)
A unifying nonlinear probabilistic epidemic model in space and time
Scientific Reports, 2021 Covid-19 epidemic dramatically relaunched the importance of mathematical modelling in supporting governments decisions to slow down the disease propagation. On the other hand, it remains a challenging task for mathematical modelling.
Roberto Beneduci +2 more
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Validation of Ensemble-Based Probabilistic Tropical Cyclone Intensity Change
Atmosphere, 2021 Although there has been substantial improvement to numerical weather prediction models, accurate predictions of tropical cyclone rapid intensification (RI) remain elusive.
Ryan D. Torn, Mark DeMaria
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Jixie qiangdu, 2022 A Bayesian model updating and damage identification method based on Markov chain sampling was proposed for damage identification of stochastics structures.
GAN Lu, CHEN Hui
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Effect of Probabilistic Similarity Measure on Metric-Based Few-Shot Classification
Applied Sciences, 2021 In developing a few-shot classification model using deep networks, the limited number of samples in each class causes difficulty in utilizing statistical characteristics of the class distributions.
Youngjae Lee, Hyeyoung Park
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Constraint-based probabilistic modeling for statistical abduction [PDF]
Machine Learning, 2010 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sato, Taisuke +2 more
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Energy Markets Forecasting. From Inferential Statistics to Machine Learning: The German Case
Energies, 2021 In this work, we investigate a probabilistic method for electricity price forecasting, which overcomes traditional ones. We start considering statistical methods for point forecast, comparing their performance in terms of efficiency, accuracy, and ...
Emma Viviani +2 more
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Epidemics, 2017 The World Health Organization and its partners are aiming to eliminate trachoma as a public health problem by 2020. In this study, we compare forecasts of TF prevalence in 2011 for 7 different statistical and mechanistic models across 9 de-identified ...
Amy Pinsent +7 more
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Statistical inference with probabilistic graphical models
, 2014 Chapter of "Statistical Physics, Optimization, Inference, and Message-Passing Algorithms", Eds.: F. Krzakala, F. Ricci-Tersenghi, L. Zdeborova, R. Zecchina, E. W. Tramel, L. F. Cugliandolo (Oxford University Press, to appear)
Drémeau, Angélique +3 more
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Where do statistical models come from? Revisiting the problem of specification
, 2006 R. A. Fisher founded modern statistical inference in 1922 and identified its fundamental problems to be: specification, estimation and distribution. Since then the problem of statistical model specification has received scant attention in the statistics ...
Spanos, Aris
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Empirical Risk Minimization for Probabilistic Grammars: Sample Complexity and Hardness of Learning [PDF]
, 2012 Probabilistic grammars are generative statistical models that are useful for compositional and sequential structures. They are used ubiquitously in computational linguistics.
Cohen, S. B., Smith, N. A.
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