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 ...

In recent years, numerous landslides on hillsides in urban and rural areas have underscored that understanding and predicting these phenomena is more than an academic curiosity—it is a human necessity ...

A new analysis of the Hubble constant to show that the Gaussian Processes data reconstruction technique may not actually be independent of all cosmological models -- and that it may be time to ...

A relatively simple statistical analysis method can more accurately predict the risk of landslides caused by heavy rain, according to a study coordinated by Brazilian researchers affiliated with the ...

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 ...

Transformations of a class of Gaussian processes to the Brownian motion are obtained by reproducing kernel Hilbert space methods. These transformations are such that the value of the transformed ...

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This research from Keio University leverages Gaussian process regression, enabling robots to intuitively adjust grip based on object properties and stiffness.