Probabilistic Parametric Curves for Sequence Modeling

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by Ronny Hug
English | 2022 | ISBN: 3731511983 | 224 Pages | True PDF | 42 MB

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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