Probabilistic Parametric Curves for Sequence Modeling

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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Bibliografiske detaljer

Hovedforfatter:	Hug, Ronny
Format:	Online
Sprog:	engelsk
Udgivet:	KIT Scientific Publishing 2022
Fag:	Probabilistische Sequenzmodellierung Stochastische Prozesse Neuronale Netzwerke Parametrische Kurven Probabilistic Sequence Modeling Stochastic Processes Neural Networks Parametric Curves thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists
Online adgang:	ONIX_20220718_9783731511984_116
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