Personal profile
Research
Filip Tronarp is a associate Senior Lecturer (Assistant Professor) at the Centre for Mathematical Sciences at Lund University with the WASP (Wallenberg AI, Autonomous Systems and Software Program). He has previously worked as a post-docoral researcher with the Methods of Machine Learning group at University of Tübingen (2020 - 2023).
Filip Tronarp received his Doctor of Science (tech) degree in Automation, Systems and Control Engineering from Aalto University in 2020 and his Master of Science degree in Engineering Mathematics from Lund University in 2016. His research interest pertains to modelling and inference in stochastic systems, and applications thereof.
Please note that the publication record on this portal may be incomplete. Refer to my google scholar profile for a more complete record, and my personal webpage for more information on my research activities.
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Collaborations the last five years
Research output
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Propagating Model Uncertainty through Filtering-based Probabilistic Numerical ODE Solvers
Yao, D., Tronarp, F. & Bosch, N., 2025, Proceedings of Machine Learning Research. Vol. 271. (Proceedings of Machine Learning Research).Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review
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Orthonormal expansions for translation-invariant kernels
Tronarp, F. & Karvonen, T., 2024 Sept, In: Journal of Approximation Theory. 302, 106055.Research output: Contribution to journal › Article › peer-review
Open Access -
Numerically robust square root implementations of statistical linear regression filters and smoothers
Tronarp, F., 2024, 32nd European Signal Processing Conference, EUSIPCO 2024 - Proceedings. European Signal Processing Conference, EUSIPCO, p. 2597-2601 5 p.Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review
Open Access -
Parallel-in-Time Probabilistic Numerical ODE Solvers
Bosch, N., Corenflos, A., Yaghoobi, F., Tronarp, F., Hennig, P. & Särkkä, S., 2024, In: Journal of Machine Learning Research. 25, p. 1-27 27 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Probabilistic ODE Solvers for Integration Error-Aware Numerical Optimal Control
Lahr, A., Tronarp, F., Bosch, N., Schmidt, J., Hennig, P. & Zeilinger, M. N., 2024, In: Proceedings of Machine Learning Research. 242, p. 1018-1032 15 p.Research output: Contribution to journal › Article › peer-review
Open Access