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.
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ISBN | 9783731511984 |
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Sprache | eng |
Cover | Kartonierter Einband (Kt) |
Verlag | Karlsruher Institut für Technologie |
Jahr | 20220712 |
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