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Probabilistic Parametric Curves for Sequence Modeling

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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 advant...

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Bibliographic Details
Main Author: Hug, Ronny (auth)
Format: Electronic Book Chapter
Language:English
Published: Karlsruhe KIT Scientific Publishing 2022
Series:Karlsruher Schriften zur Anthropomatik 54
Subjects:
Maths for computer scientists
Probabilistische Sequenzmodellierung
Stochastische Prozesse
Neuronale Netzwerke
Parametrische Kurven
Probabilistic Sequence Modeling
Stochastic Processes
Neural Networks
Parametric Curves
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