
Hug, RonnyProbabilistic Parametric Curves for Sequence Modeling
Kartoniert, KIT Scientific Publishing (2022)
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This work proposes a probabilistic extension to Bézier curves as a basis for effectively modeling stochastic processes with a bounded index set. The proposed stochastic process model is based on Mixture Density Networks and Bézier curves with Gaussian random variables as control points. A key advantage of this model is given by the ability to generate multi-mode predictions in a single inference step, thus avoiding the need for Monte Carlo simulation.
Seitenanzahl
226 S.
Sprache
Englisch
Verlag
KIT Scientific Publishing (2022)
Gewicht
430 g
ISBN-13
978-3-7315-1198-4
Titelnr.
96026407
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