Parallel and distributed computing for Bayesian graphical models

Särkkä, Simo (Principal investigator)
Merkatas, Christos (Project Member)
Yamin, Abubakar (Project Member)
Corenflos, Adrien (Project Member)
Ma, Xiaofeng (Project Member)
Emzir, Muhammad (Project Member)
Yaghoobi, Fatemeh (Project Member)
Hassan, Syeda Sakira (Project Member)

Department of Electrical Engineering and Automation

3 Conference article in proceedings
3 Article

6 results

2022
De-Sequentialized Monte Carlo: a parallel-in-time particle smoother
Corenflos, A., Särkkä, S. & Chopin, N., 1 Aug 2022, In: Journal of Machine Learning Research. 23, 39 p.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
44 Downloads (Pure)
Temporal Gaussian Process Regression in Logarithmic Time
Corenflos, A., Zhao, Z. & Sarkka, S., 2022, 2022 25th International Conference on Information Fusion, FUSION 2022. International Society of Information Fusion, p. 1-5 5 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Open Access
2 Citations (Scopus)
2021
Differentiable Particle Filtering via Entropy-Regularized Optimal Transport
Corenflos, A., Thornton, J., Deligiannidis, G. & Doucet, A., 2021, Proceedings of Machine Learning Research. Meila, M. & Zhang, T. (eds.). JMLR, 12 p. (Proceedings of Machine Learning Research; vol. 139).
Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Open Access
2020
Enhancing industrial X-ray tomography by data-centric statistical methods
Suuronen, J., Emzir, M., Lasanen, S., Särkkä, S. & Roininen, L., 16 Oct 2020, In: Data-Centric Engineering. 1, 3, 17 p., e10.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
6 Citations (Scopus)

70 Downloads (Pure)
Non-stationary multi-layered Gaussian priors for Bayesian inversion
Emzir, M., Lasanen, S., Purisha, Z., Roininen, L. & Särkkä, S., 3 Dec 2020, In: Inverse Problems. 37, 1, 26 p., 015002.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
6 Citations (Scopus)

83 Downloads (Pure)
Parameter estimation in non-linear state-space models by automatic differentiation of non-linear kalman filters
Gorad, A., Zhao, Z. & Särkkä, S., Sept 2020, Proceedings of the 2020 IEEE 30th International Workshop on Machine Learning for Signal Processing, MLSP 2020. IEEE, 6 p. 9231844. (IEEE International Workshop on Machine Learning for Signal Processing).
Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Open Access
File
524 Downloads (Pure)

Parallel and distributed computing for Bayesian graphical models

Research output

Search results

De-Sequentialized Monte Carlo: a parallel-in-time particle smoother

Temporal Gaussian Process Regression in Logarithmic Time

Differentiable Particle Filtering via Entropy-Regularized Optimal Transport

Enhancing industrial X-ray tomography by data-centric statistical methods

Non-stationary multi-layered Gaussian priors for Bayesian inversion

Parameter estimation in non-linear state-space models by automatic differentiation of non-linear kalman filters