Introducing Probabilistic Bézier Curves for N-Step Sequence Prediction

2020-06-02

Proceedings of the AAAI Conference on Artificial Intelligence, 34

Volume

Vol. 34 No. 06: AAAI-20 Technical Tracks 6

AAAI Technical Track: Reasoning under Uncertainty

Representations of sequential data are commonly based on the assumption that observed sequences are realizations of an unknown underlying stochastic process, where the learning problem includes determination of the model parameters. In this context, a model must be able to capture the multi-modal nature of the data, without blurring between single modes. This paper proposes probabilistic B'{e}zier curves (

10.1609/aaai.v34i06.6576