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Dynamic time warping (DTW) is a useful method for aligning, comparing and combining time series, but it requires them to live in …

Learning physically structured representations of dynamical systems that include contact between different objects is an important …

Gaussian processes are a versatile framework for learning unknown functions in a manner that permits one to utilize prior information …

As Gaussian processes are integrated into increasingly complex problem settings, analytic solutions to quantities of interest become …

Gaussian processes are an effective model class for learning unknown functions, particularly in settings where accurately representing …

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