HIGHLIGHTS
- who: Dmytro Velychko and collaborators from the Department of Psychology, University of Marburg, Gutenbergstr18, Marburg, Germany have published the research: Making the Coupled Gaussian Process Dynamical Model Modular and Scalable with Variational Approximations, in the Journal: Entropy 2018, 20, 724 of /2018/
- what: The aim of the approximation is threefold: first to reduce training time of the model; second to enable modular re-use of learned dynamics; and third to store these learned dynamics compactly. The authors show that the CGPDM outperforms several other MP models on movement trajectory prediction. For this paper, an MP . . .
If you want to have access to all the content you need to log in!
Thanks :)
If you don't have an account, you can create one here.