9783731511984.pdf
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...
| Γλώσσα: | English |
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| Έκδοση: |
KIT Scientific Publishing
2022
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| Διαθέσιμο Online: | https://doi.org/10.5445/KSP/1000146434 |
| Περίληψη: | 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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