Probabilistic Parametric Curves for Sequence Modeling - Ronny Hug
-25% koodilla BOOKS
Toimitus 12-18 arkipäivässä
30 päivän palautusoikeus
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 ... Täydellinen kuvaus
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Kuvaus
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.
Lisätietoja
| Kirjoittaja | Ronny Hug |
|---|---|
| Julkaisija | Karlsruher Institut für Technologie |
| Julkaisuvuosi | 2022 |
| Kannen tyyppi | Pehmeäkantinen |
| EAN | 9783731511984 |