Filip Tronarp

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 47

Top Topics

State Estimation

Particle Filtering

Differential Equations

Top Venues

IEEE Signal Process. Lett.

Publications

Filip Tronarp, Toni Karvonen
Orthonormal expansions for translation-invariant kernels. J. Approx. Theory 302 (2024)
Amon Lahr, Filip Tronarp, Nathanael Bosch, Jonathan Schmidt, Philipp Hennig, Melanie N. Zeilinger
Probabilistic ODE solvers for integration error-aware numerical optimal control. L4DC (2024)
Filip Tronarp
Numerically robust square root implementations of statistical linear regression filters and smoothers. CoRR (2024)
Tony Stillfjord, Filip Tronarp
Computing the matrix exponential and the Cholesky factor of a related finite horizon Gramian. CoRR (2023)
Jonathan Schmidt, Philipp Hennig, Jörg Nick, Filip Tronarp
The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions. CoRR (2023)
Toni Karvonen, Jon Cockayne, Filip Tronarp, Simo Särkkä
A probabilistic Taylor expansion with Gaussian processes. Trans. Mach. Learn. Res. 2023 (2023)
Jonathan Schmidt, Philipp Hennig, Jörg Nick, Filip Tronarp
The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions. NeurIPS (2023)
Nathanael Bosch, Philipp Hennig, Filip Tronarp
Probabilistic Exponential Integrators. NeurIPS (2023)
Nathanael Bosch, Adrien Corenflos, Fatemeh Yaghoobi, Filip Tronarp, Philipp Hennig, Simo Särkkä
Parallel-in-Time Probabilistic Numerical ODE Solvers. CoRR (2023)
Nathanael Bosch, Philipp Hennig, Filip Tronarp
Probabilistic Exponential Integrators. CoRR (2023)
Nathanael Bosch, Filip Tronarp, Philipp Hennig
Pick-and-Mix Information Operators for Probabilistic ODE Solvers. AISTATS (2022)
Filip Tronarp, Nathanael Bosch, Philipp Hennig
Fenrir: Physics-Enhanced Regression for Initial Value Problems. CoRR (2022)
Filip Tronarp, Nathanael Bosch, Philipp Hennig
Fenrir: Physics-Enhanced Regression for Initial Value Problems. ICML (2022)
Filip Tronarp, Toni Karvonen
Orthonormal Expansions for Translation-Invariant Kernels. CoRR (2022)
Filip Tronarp, Simo Särkkä
Continuous-Discrete Filtering and Smoothing on Submanifolds of Euclidean Space. FUSION (2022)
Nathanael Bosch, Philipp Hennig, Filip Tronarp
Calibrated Adaptive Probabilistic ODE Solvers. AISTATS (2021)
Nathanael Bosch, Filip Tronarp, Philipp Hennig
Pick-and-Mix Information Operators for Probabilistic ODE Solvers. CoRR (2021)
Toni Karvonen, Jon Cockayne, Filip Tronarp, Simo Särkkä
A Probabilistic Taylor Expansion with Applications in Filtering and Differential Equations. CoRR (2021)
Filip Tronarp, Simo Särkkä, Philipp Hennig
Bayesian ODE solvers: the maximum a posteriori estimate. Stat. Comput. 31 (3) (2021)
Rui Gao, Filip Tronarp, Simo Särkkä
Variable Splitting Methods for Constrained State Estimation in Partially Observed Markov Processes. CoRR (2020)
Rui Gao, Filip Tronarp, Simo Särkkä
Variable Splitting Methods for Constrained State Estimation in Partially Observed Markov Processes. IEEE Signal Process. Lett. 27 (2020)
Nathanael Bosch, Philipp Hennig, Filip Tronarp
Calibrated Adaptive Probabilistic ODE Solvers. CoRR (2020)
Toni Karvonen, George Wynne, Filip Tronarp, Chris J. Oates, Simo Särkkä
Maximum Likelihood Estimation and Uncertainty Quantification for Gaussian Process Approximation of Deterministic Functions. SIAM/ASA J. Uncertain. Quantification 8 (3) (2020)
Zheng Zhao, Filip Tronarp, Roland Hostettler, Simo Särkkä
State-Space Gaussian Process for Drift Estimation in Stochastic Differential Equations. ICASSP (2020)
Filip Tronarp, Simo Särkkä, Philipp Hennig
Bayesian ODE Solvers: The Maximum A Posteriori Estimate. CoRR (2020)
Toni Karvonen, George Wynne, Filip Tronarp, Chris J. Oates, Simo Särkkä
Maximum likelihood estimation and uncertainty quantification for Gaussian process approximation of deterministic functions. CoRR (2020)
Roland Hostettler, Filip Tronarp, Ángel F. García-Fernández, Simo Särkkä
Importance Densities for Particle Filtering Using Iterated Conditional Expectations. IEEE Signal Process. Lett. 27 (2020)
Rui Gao, Filip Tronarp, Simo Särkkä
-Regularized State Estimation. IEEE Trans. Signal Process. 67 (19) (2019)
Filip Tronarp, Simo Särkkä
Iterative statistical linear regression for Gaussian smoothing in continuous-time non-linear stochastic dynamic systems. Signal Process. 159 (2019)
Rui Gao, Filip Tronarp, Simo Särkkä
-Regularized State Estimation. CoRR (2019)
Rui Gao, Filip Tronarp, Zheng Zhao, Simo Särkkä
Regularized State Estimation And Parameter Learning Via Augmented Lagrangian Kalman Smoother Method. MLSP (2019)
Ángel F. García-Fernández, Filip Tronarp, Simo Särkkä
Gaussian Target Tracking With Direction-of-Arrival von Mises-Fisher Measurements. IEEE Trans. Signal Process. 67 (11) (2019)
Filip Tronarp, Hans Kersting, Simo Särkkä, Philipp Hennig
Probabilistic solutions to ordinary differential equations as nonlinear Bayesian filtering: a new perspective. Stat. Comput. 29 (6) (2019)
Toni Karvonen, Filip Tronarp, Simo Särkkä
Asymptotics of Maximum Likelihood Parameter Estimates For Gaussian Processes: The Ornstein-Uhlenbeck Prior. MLSP (2019)
Ángel F. García-Fernández, Filip Tronarp, Simo Särkkä
Gaussian Process Classification Using Posterior Linearization. IEEE Signal Process. Lett. 26 (5) (2019)
Filip Tronarp, Simo Särkkä
Updates in Bayesian Filtering by Continuous Projections on a Manifold of Densities. ICASSP (2019)
Filip Tronarp, Toni Karvonen, Simo Särkkä
Student's $t$-Filters for Noise Scale Estimation. IEEE Signal Process. Lett. 26 (2) (2019)
Roland Hostettler, Ángel F. García-Fernández, Filip Tronarp, Simo Särkkä
Joint Calibration of Inertial Sensors and Magnetometers using von Mises-Fisher Filtering and Expectation Maximization. FUSION (2019)
Filip Tronarp, Toni Karvonen, Simo Särkkä
Mixture Representation of the MatéRn class with Applications in State Space Approximations and Bayesian quadrature. MLSP (2018)
Filip Tronarp, Roland Hostettler, Simo Särkkä
for Reference Vector Tracking. FUSION (2018)
Ángel F. García-Fernández, Filip Tronarp, Simo Särkkä
Gaussian process classification using posterior linearisation. CoRR (2018)
Filip Tronarp, Narayan Puthanmadam Subramaniyam, Simo Särkkä, Lauri Parkkonen
Tracking of dynamic functional connectivity from MEG data with Kalman filtering. EMBC (2018)
Rui Gao, Filip Tronarp, Simo Särkkä
Combined Analysis-L1 and Total Variation ADMM with Applications to MEG Brain Imaging and Signal Reconstruction. EUSIPCO (2018)
Filip Tronarp, Simo Särkkä
Non-Linear Continuous-Discrete Smoothing by Basis Function Expansions of Brownian Motion. FUSION (2018)
Filip Tronarp, Ángel F. García-Fernández, Simo Särkkä
Iterative Filtering and Smoothing in Nonlinear and Non-Gaussian Systems Using Conditional Moments. IEEE Signal Process. Lett. 25 (3) (2018)
Jakub Prüher, Filip Tronarp, Toni Karvonen, Simo Särkkä, Ondrej Straka
Student-t process quadratures for filtering of non-linear systems with heavy-tailed noise. FUSION (2017)
Filip Tronarp, Roland Hostettler, Simo Särkkä
Sigma-point filtering for nonlinear systems with non-additive heavy-tailed noise. FUSION (2016)