The Annals of Probability, Vol. 1, No. 6 (Dec., 1973), pp. 968-981 (14 pages) This paper is mainly a survey of results on the problem of finding necessary and sufficient conditions for a Gaussian ...
Gaussian processes offer a versatile framework to model and analyse continuous random phenomena, making them particularly useful in quantifying the probability of ruin in financial and insurance ...
Random fields and Gaussian processes constitute fundamental frameworks in modern probability theory and spatial statistics, providing robust tools for modelling complex dependencies over space and ...
A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the price of a house based on its square footage, age, number of bedrooms and ...
All sorts of physical processes in this analog world exhibit some degree of randomness. Think of noise, for example. Many noisy processes are described by Gaussian probability distributions. We should ...
Despite growing interest in the use of complex models, such as machine learning (ML) models, for credit underwriting, ML models are difficult to interpret, and it is possible for them to learn ...
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Pantelis Samartsidis, Claudia R. Eickhoff, Simon B. Eickhoff, Tor D. Wager, Lisa Feldman Barrett, Shir Atzil, Timothy D. Johnson, Thomas E. Nichols Journal of the ...
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