Streaming Principal Component Analysis From Incomplete Data

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Publications associées (32)

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In this work we introduce a manifold learning-based method for uncertainty quantification (UQ) in systems describing complex spatiotemporal processes. Our first objective is to identify the embedding of a set of high-dimensional data representing quantitie ...

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Multiscale phenomena are involved in countless problems in fluid mechanics. Coating flows are known to exhibit a broad variety of patterns, such as wine tears in a glass and dripping of fresh paint applied on a wall. Coating flows are typically modeled und ...

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The utility of machine learning in understanding the motor system is promising a revolution in how to collect, measure, and analyze data. The field of movement science already elegantly incorporates theory and engineering principles to guide experimental w ...

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The overground speed is a key component of running analysis. Today, most speed estimation wearable systems are based on GNSS technology. However, these devices can suffer from sparse communication with the satellites and have a high-power consumption. In t ...

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Data & Figures on the Multiscale Spatiotemporal Characterization of Embodied Environmental Efficiency of Building Structures in Geneva from 1850 to 2018

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Process data, figures, and figure data resulting from the study on Multiscale Spatiotemporal Characterization of Embodied Environmental Efficiency of Building Structures in Geneva from 1850 to 2018. ...

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