Marcel Hirt, Petros Dellaportas. Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers. In Kamalika Chaudhuri, Masashi Sugiyama, editors, The 22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 16-18 April 2019, Naha, Okinawa, Japan. Volume 89 of Proceedings of Machine Learning Research, pages 76-86, PMLR, 2019. [doi]
@inproceedings{HirtD19,
title = {Scalable Bayesian Learning for State Space Models using Variational Inference with SMC Samplers},
author = {Marcel Hirt and Petros Dellaportas},
year = {2019},
url = {http://proceedings.mlr.press/v89/hirt19a.html},
researchr = {https://researchr.org/publication/HirtD19},
cites = {0},
citedby = {0},
pages = {76-86},
booktitle = {The 22nd International Conference on Artificial Intelligence and Statistics, AISTATS 2019, 16-18 April 2019, Naha, Okinawa, Japan},
editor = {Kamalika Chaudhuri and Masashi Sugiyama},
volume = {89},
series = {Proceedings of Machine Learning Research},
publisher = {PMLR},
}