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 this article, we derive a Stratonovich and Skorohod-type change of variables formula for a multidimensional Gaussian process with low Hölder regularity γ (typically γ ≤ 1/4). To this aim, we ...
We propose a nested Gaussian process (nGP) as a locally adaptive prior for Bayesian nonparametric regression. Specified through a set of stochastic differential equations (SDEs), the nGP imposes a ...
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New adaptive system lets robots replicate human touch with far less training data
Researchers in Japan have developed an adaptive motion reproduction system that allows robots to ...
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Adaptive motion system helps robots achieve human-like dexterity with minimal data
Despite rapid robotic automation advancements, most systems struggle to adapt their pre-trained movements to dynamic ...
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