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Found 3 papers, 1 papers with code
Memory-Based Dual Gaussian Processes for Sequential Learning
Sequential learning with Gaussian processes (GPs) is challenging when access to past data is limited, for example, in continual and active learning.
Learning relevant contextual variables within Bayesian Optimization
Contextual Bayesian Optimization (CBO) efficiently optimizes black-box functions with respect to design variables, while simultaneously integrating contextual information regarding the environment, such as experimental conditions.
Large-Scale Cox Process Inference using Variational Fourier Features
This allows us to formulate a grid-free approximation that scales well with the number of data points and the size of the domain.
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