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Data-efficient learning algorithms are essential in many practical applications where data collection is expensive, e.g., in robotics …

Barycentric averaging is a principled way of summarizing populations of measures. Existing algorithms for estimating barycenters …

Gaussian processes are the gold standard for many real-world modeling problems, especially in cases where a model’s success …

We present a Bayesian non-parametric way of inferring stochastic differential equations for both regression tasks and continuous-time …

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

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