Online Resource
Karlsruhe : KIT Scientific Publishing
UID:
edoccha_9960795695902883
Format:
1 electronic resource (226 p.)
ISBN:
1000146434
Series Statement:
Karlsruher Schriften zur Anthropomatik
Content:
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.
Note:
English
Additional Edition:
ISBN 3-7315-1198-3
Language:
English
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