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Browsing by Keyword "Gaussian process regression"

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Title: Accelerating Bayesian Optimization Structure Search with Transfer Learning Author(s): Sten, Nuutti Date: 2021-01-25 Perustieteiden korkeakoulu | Master's thesis
Title: Approximate state-space Gaussian processes via spectral transformation Author(s): Karvonen, Toni; Särkkä, Simo Date: 2016-11-08 Series: Proceedings of the 2016 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2016, Volume 2016-November, IEEE International Workshop on Machine Learning for Signal Processing
Title: Deep state-space Gaussian processes Author(s): Zhao, Zheng; Emzir, Muhammad; Särkkä, Simo Date: 2021-11 Series: STATISTICS AND COMPUTING, Volume 31, issue 6
Title: Hilbert space methods for reduced-rank Gaussian process regression Author(s): Solin, Arno; Särkkä, Simo Date: 2019 Series: STATISTICS AND COMPUTING
Title: Hilbert Space Methods in Infinite-Dimensional Kalman Filtering Author(s): Solin, Arno Date: 2012 | Master's thesis
Title: Machine learning as a tool to engineer microstructures: Morphological prediction of tannin-based colloids using Bayesian surrogate models Author(s): Jin, Soo Ah; Kämäräinen, Tero; Rinke, Patrick; Rojas, Orlando J.; Todorovic, Milica Date: 2022 Series: MRS Bulletin, Volume 47
Title: Machine learning based integrated feature selection approach for improved electricity demand forecasting in decentralized energy systems Author(s): Eseye, Abinet Tesfaye; Lehtonen, Matti; Tukia, Toni; Uimonen, Semen; Millar, R. John Date: 2019-01-01 Series: IEEE Access, Volume 7
Title: Mixture representation of the matérn class with applications in state space approximations and Bayesian quadrature Author(s): Tronarp, Filip; Karvonen, Toni; Särkkä, Simo Date: 2018-10-31 Series: Proceedings of the 2018 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2018, Volume 2018-September, IEEE International Workshop on Machine Learning for Signal Processing
Title: State-space Gaussian Process for Drift Estimation in Stochastic Differential Equations Author(s): Zhao, Zheng; Tronarp, Filip; Hostettler, Roland; Särkkä, Simo Date: 2020-05 Series: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020, Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing
Title: Utility of remotely sensed spectral information in forest variable estimation Author(s): Halme, Eelis Date: 2018-12-10 Insinööritieteiden korkeakoulu | Master's thesis