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 ...
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 ...
This research from Keio University leverages Gaussian process regression, enabling robots to intuitively adjust grip based on ...
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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 ...
Researchers develop an adaptive motion system that allows robots to generate human-like movements with minimal data ...
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