フォロー
Filip Tronarp
Filip Tronarp
Associate Senior Lecturer / Assistant Professor, Lund University
確認したメール アドレス: matstat.lu.se - ホームページ
タイトル
引用先
引用先
Probabilistic solutions to ordinary differential equations as nonlinear Bayesian filtering: a new perspective
F Tronarp, H Kersting, S Särkkä, P Hennig
Statistics and Computing 29 (6), 1297-1315, 2019
632019
Iterative Filtering and Smoothing in Nonlinear and Non-Gaussian Systems Using Conditional Moments
F Tronarp, ÁF García-Fernández, S Särkkä
IEEE Signal Processing Letters 25 (3), 408-412, 2018
472018
Maximum likelihood estimation and uncertainty quantification for Gaussian process approximation of deterministic functions
T Karvonen, G Wynne, F Tronarp, C Oates, S Särkkä
SIAM/ASA Journal on Uncertainty Quantification 8 (3), 926-958, 2020
422020
Bayesian ode solvers: The maximum a posteriori estimate
F Tronarp, S Särkkä, P Hennig
Statistics and Computing 31 (3), 1-18, 2021
412021
Sigma-point filtering for nonlinear systems with non-additive heavy-tailed noise
F Tronarp, R Hostettler, S Särkkä
2016 19th International Conference on Information Fusion (FUSION), 1859-1866, 2016
412016
Calibrated adaptive probabilistic ODE solvers
N Bosch, P Hennig, F Tronarp
International Conference on Artificial Intelligence and Statistics, 3466-3474, 2021
262021
Student's -Filters for Noise Scale Estimation
F Tronarp, T Karvonen, S Särkkä
IEEE Signal Processing Letters 26 (2), 352-356, 2019
202019
Iterated Extended Kalman Smoother-Based Variable Splitting for -Regularized State Estimation
R Gao, F Tronarp, S Särkkä
IEEE Transactions on Signal Processing 67 (19), 5078-5092, 2019
182019
Gaussian target tracking with direction-of-arrival von Mises–Fisher measurements
AF Garcia-Fernandez, F Tronarp, S Särkkä
IEEE Transactions on Signal Processing 67 (11), 2960-2972, 2019
182019
Student-t process quadratures for filtering of non-linear systems with heavy-tailed noise
J Prüher, F Tronarp, T Karvonen, S Särkkä, O Straka
2017 20th International Conference on Information Fusion (Fusion), 1-8, 2017
172017
Fenrir: Physics-Enhanced Regression for Initial Value Problems
F Tronarp, N Bosch, P Hennig
International Conference on Machine Learning, 21776-21794, 2022
92022
Iterative statistical linear regression for Gaussian smoothing in continuous-time non-linear stochastic dynamic systems
F Tronarp, S Särkkä
Signal Processing 159, 1-12, 2019
92019
Pick-and-mix information operators for probabilistic ODE solvers
N Bosch, F Tronarp, P Hennig
International Conference on Artificial Intelligence and Statistics, 10015-10027, 2022
82022
Gaussian Process Classification Using Posterior Linearization
ÁF García-Fernández, F Tronarp, S Särkkä
IEEE Signal Processing Letters 26 (5), 735-739, 2019
82019
Tracking of dynamic functional connectivity from MEG data with Kalman filtering
F Tronarp, NP Subramaniyam, S Särkkä, L Parkkonen
2018 40th Annual International Conference of the IEEE Engineering in …, 2018
82018
State-Space Gaussian Process for Drift Estimation in Stochastic Differential Equations
Z Zhao, F Tronarp, R Hostettler, S Särkkä
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
72020
Combined Analysis-L1 and Total Variation ADMM with Applications to MEG Brain Imaging and Signal Reconstruction
R Gao, F Tronarp, S Särkkä
2018 26th European Signal Processing Conference (EUSIPCO), 1930-1934, 2018
72018
The rank-reduced Kalman filter: Approximate dynamical-low-rank filtering in high dimensions
J Schmidt, P Hennig, J Nick, F Tronarp
Advances in Neural Information Processing Systems 36, 2024
62024
Importance Densities for Particle Filtering Using Iterated Conditional Expectations
R Hostettler, F Tronarp, ÁF García-Fernández, S Särkkä
IEEE Signal Processing Letters 27, 211-215, 2020
62020
Mixture representation of the Matérn class with applications in state space approximations and Bayesian quadrature
F Tronarp, T Karvonen, S Särkkä
2018 IEEE 28th International Workshop on Machine Learning for Signal …, 2018
62018
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