Results 11 to 20 of about 389,202 (312)
Random Fields in Physics, Biology and Data Science
Frontiers in Physics, 2021 A random field is the representation of the joint probability distribution for a set of random variables. Markov fields, in particular, have a long standing tradition as the theoretical foundation of many applications in statistical physics and ...
Enrique Hernández-Lemus +1 more
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Inducing features of random fields [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997 34 pages, compressed ...
Stephen Della Pietra +2 more
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Random fields and random sampling [PDF]
Kybernetika, 2020 The authors study the limit in distribution of the maximum of a stationary bivariate real random field, sampled at double random times under some dependence conditions. It is shown that the limit distribution is a max-semistable distribution when the random samples have a geometric growth pattern. When the random field is sampled at double random times,
Sandra Dias, Maria da Graça Temido
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Frontiers in Earth Science, 2022 The 2019 Le Teil earthquake is an illustrative example of a moderate (MW 4.9) yet damaging event, occurring at shallow depth (≈1 km) in a region with little to no geophysical data available.
Fanny Lehmann +4 more
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Applied Sciences, 2023 Natural disasters, when and where they occur, often cause serious social and economic consequences, which require an urgent solution to the problem. In particular, Greece, which is characterized by a complex geological structure and intense tectonic ...
Nikolaos Alamanis, Panagiotis Dakoulas
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Computers & Chemical Engineering, 2022 We present a new modeling paradigm for optimization that we call random field optimization. Random fields are a powerful modeling abstraction that aims to capture the behavior of random variables that live on infinite-dimensional spaces (e.g., space and time) such as stochastic processes (e.g., time series, Gaussian processes, and Markov processes ...
Joshua L. Pulsipher +2 more
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Spatial Warped Gaussian Processes: Estimation and Efficient Field Reconstruction
Entropy, 2021 A class of models for non-Gaussian spatial random fields is explored for spatial field reconstruction in environmental and sensor network monitoring.
Gareth W. Peters +3 more
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The behavior of partially coherent twisted space-time beams in atmospheric turbulence
Frontiers in Physics, 2023 We study how atmospheric turbulence affects twisted space-time beams, which are non-stationary random optical fields whose space and time dimensions are coupled with a stochastic twist.
Milo W. Hyde IV
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Kernel Distance Measures for Time Series, Random Fields and Other Structured Data
Frontiers in Applied Mathematics and Statistics, 2021 This paper introduces kdiff, a novel kernel-based measure for estimating distances between instances of time series, random fields and other forms of structured data.
Srinjoy Das +2 more
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Architecture, Civil Engineering, Environment, 2023 The paper presents a proprietary procedure for the analysis of normal stress distributions in post-tensioned cross-sections. It has a significant advantage over conventional commonly used approaches based solely on the envelope analysis as it provides ...
Owerko Piotr
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