Filip Tronarp - RankMe

55 papers A* 3A 2C 6Misc 2Journal 34Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Barron-Wiener-Laguerre models. CoRR Rahul Manavalan, Filip Tronarp
2025	J	`jnl`	Numerically robust Gaussian state estimation with singular observation noise. CoRR Nicholas Krämer, Filip Tronarp
2025	—	`conf`	Propagating Model Uncertainty through Filtering-based Probabilistic Numerical ODE Solvers. ProbNum Dingling Yao, Filip Tronarp, Nathanael Bosch
2025	J	`jnl`	Propagating Model Uncertainty through Filtering-based Probabilistic Numerical ODE Solvers. CoRR Dingling Yao, Filip Tronarp, Nathanael Bosch
2025	J	`jnl`	The two filter formula reconsidered: Smoothing in partially observed Gauss-Markov models without information parametrization. CoRR Filip Tronarp
2024	—	`conf`	Numerically Robust Square Root Implementations of Statistical Linear Regression Filters and Smoothers. EUSIPCO Filip Tronarp
2024	J	`jnl`	Numerically robust square root implementations of statistical linear regression filters and smoothers. CoRR Filip Tronarp
2024	J	`jnl`	Orthonormal expansions for translation-invariant kernels. J. Approx. Theory Filip Tronarp, Toni Karvonen
2024	J	`jnl`	Parallel-in-Time Probabilistic Numerical ODE Solvers. J. Mach. Learn. Res. Nathanael Bosch, Adrien Corenflos, Fatemeh Yaghoobi, Filip Tronarp, Philipp Hennig, Simo Särkkä
2024	J	`jnl`	Probabilistic ODE Solvers for Integration Error-Aware Numerical Optimal Control. CoRR Amon Lahr, Filip Tronarp, Nathanael Bosch, Jonathan Schmidt, Philipp Hennig, Melanie N. Zeilinger
2024	—	`conf`	Probabilistic ODE solvers for integration error-aware numerical optimal control. L4DC Amon Lahr, Filip Tronarp, Nathanael Bosch, Jonathan Schmidt, Philipp Hennig, Melanie N. Zeilinger
2023	J	`jnl`	A probabilistic Taylor expansion with Gaussian processes. Trans. Mach. Learn. Res. Toni Karvonen, Jon Cockayne, Filip Tronarp, Simo Särkkä
2023	J	`jnl`	Computing the matrix exponential and the Cholesky factor of a related finite horizon Gramian. CoRR Tony Stillfjord, Filip Tronarp
2023	J	`jnl`	Parallel-in-Time Probabilistic Numerical ODE Solvers. CoRR Nathanael Bosch, Adrien Corenflos, Fatemeh Yaghoobi, Filip Tronarp, Philipp Hennig, Simo Särkkä
2023	A*	`conf`	Probabilistic Exponential Integrators. NeurIPS Nathanael Bosch, Philipp Hennig, Filip Tronarp
2023	J	`jnl`	Probabilistic Exponential Integrators. CoRR Nathanael Bosch, Philipp Hennig, Filip Tronarp
2023	A*	`conf`	The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions. NeurIPS Jonathan Schmidt, Philipp Hennig, Jörg Nick, Filip Tronarp
2023	J	`jnl`	The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions. CoRR Jonathan Schmidt, Philipp Hennig, Jörg Nick, Filip Tronarp
2022	C	`conf`	Continuous-Discrete Filtering and Smoothing on Submanifolds of Euclidean Space. FUSION Filip Tronarp, Simo Särkkä
2022	A*	`conf`	Fenrir: Physics-Enhanced Regression for Initial Value Problems. ICML Filip Tronarp, Nathanael Bosch, Philipp Hennig
2022	J	`jnl`	Fenrir: Physics-Enhanced Regression for Initial Value Problems. CoRR Filip Tronarp, Nathanael Bosch, Philipp Hennig
2022	J	`jnl`	Orthonormal Expansions for Translation-Invariant Kernels. CoRR Filip Tronarp, Toni Karvonen
2022	A	`conf`	Pick-and-Mix Information Operators for Probabilistic ODE Solvers. AISTATS Nathanael Bosch, Filip Tronarp, Philipp Hennig
2021	J	`jnl`	A Probabilistic Taylor Expansion with Applications in Filtering and Differential Equations. CoRR Toni Karvonen, Jon Cockayne, Filip Tronarp, Simo Särkkä
2021	J	`jnl`	Bayesian ODE solvers: the maximum a posteriori estimate. Stat. Comput. Filip Tronarp, Simo Särkkä, Philipp Hennig
2021	A	`conf`	Calibrated Adaptive Probabilistic ODE Solvers. AISTATS Nathanael Bosch, Philipp Hennig, Filip Tronarp
2021	J	`jnl`	Pick-and-Mix Information Operators for Probabilistic ODE Solvers. CoRR Nathanael Bosch, Filip Tronarp, Philipp Hennig
2020	J	`jnl`	Bayesian ODE Solvers: The Maximum A Posteriori Estimate. CoRR Filip Tronarp, Simo Särkkä, Philipp Hennig
2020	J	`jnl`	Calibrated Adaptive Probabilistic ODE Solvers. CoRR Nathanael Bosch, Philipp Hennig, Filip Tronarp
2020	J	`jnl`	Importance Densities for Particle Filtering Using Iterated Conditional Expectations. IEEE Signal Process. Lett. Roland Hostettler, Filip Tronarp, Ángel F. García-Fernández, Simo Särkkä
2020	J	`jnl`	Maximum Likelihood Estimation and Uncertainty Quantification for Gaussian Process Approximation of Deterministic Functions. SIAM/ASA J. Uncertain. Quantification Toni Karvonen, George Wynne, Filip Tronarp, Chris J. Oates, Simo Särkkä
2020	J	`jnl`	Maximum likelihood estimation and uncertainty quantification for Gaussian process approximation of deterministic functions. CoRR Toni Karvonen, George Wynne, Filip Tronarp, Chris J. Oates, Simo Särkkä
2020	Misc	`conf`	State-Space Gaussian Process for Drift Estimation in Stochastic Differential Equations. ICASSP Zheng Zhao, Filip Tronarp, Roland Hostettler, Simo Särkkä
2020	J	`jnl`	Variable Splitting Methods for Constrained State Estimation in Partially Observed Markov Processes. CoRR Rui Gao, Filip Tronarp, Simo Särkkä
2020	J	`jnl`	Variable Splitting Methods for Constrained State Estimation in Partially Observed Markov Processes. IEEE Signal Process. Lett. Rui Gao, Filip Tronarp, Simo Särkkä
2019	—	`conf`	Asymptotics of Maximum Likelihood Parameter Estimates For Gaussian Processes: The Ornstein-Uhlenbeck Prior. MLSP Toni Karvonen, Filip Tronarp, Simo Särkkä
2019	J	`jnl`	Gaussian Process Classification Using Posterior Linearization. IEEE Signal Process. Lett. Ángel F. García-Fernández, Filip Tronarp, Simo Särkkä
2019	J	`jnl`	Gaussian Target Tracking With Direction-of-Arrival von Mises-Fisher Measurements. IEEE Trans. Signal Process. Ángel F. García-Fernández, Filip Tronarp, Simo Särkkä
2019	J	`jnl`	Iterated Extended Kalman Smoother-Based Variable Splitting for L IEEE Trans. Signal Process. Rui Gao, Filip Tronarp, Simo Särkkä
2019	J	`jnl`	Iterated Extended Kalman Smoother-based Variable Splitting for L CoRR Rui Gao, Filip Tronarp, Simo Särkkä
2019	J	`jnl`	Iterative statistical linear regression for Gaussian smoothing in continuous-time non-linear stochastic dynamic systems. Signal Process. Filip Tronarp, Simo Särkkä
2019	C	`conf`	Joint Calibration of Inertial Sensors and Magnetometers using von Mises-Fisher Filtering and Expectation Maximization. FUSION Roland Hostettler, Ángel F. García-Fernández, Filip Tronarp, Simo Särkkä
2019	J	`jnl`	Probabilistic solutions to ordinary differential equations as nonlinear Bayesian filtering: a new perspective. Stat. Comput. Filip Tronarp, Hans Kersting, Simo Särkkä, Philipp Hennig
2019	—	`conf`	Regularized State Estimation And Parameter Learning Via Augmented Lagrangian Kalman Smoother Method. MLSP Rui Gao, Filip Tronarp, Zheng Zhao, Simo Särkkä
2019	J	`jnl`	Student's $t$-Filters for Noise Scale Estimation. IEEE Signal Process. Lett. Filip Tronarp, Toni Karvonen, Simo Särkkä
2019	Misc	`conf`	Updates in Bayesian Filtering by Continuous Projections on a Manifold of Densities. ICASSP Filip Tronarp, Simo Särkkä
2018	—	`conf`	Combined Analysis-L1 and Total Variation ADMM with Applications to MEG Brain Imaging and Signal Reconstruction. EUSIPCO Rui Gao, Filip Tronarp, Simo Särkkä
2018	C	`conf`	Continuous-Discrete von Mises-Fisher Filtering on S FUSION Filip Tronarp, Roland Hostettler, Simo Särkkä
2018	J	`jnl`	Gaussian process classification using posterior linearisation. CoRR Ángel F. García-Fernández, Filip Tronarp, Simo Särkkä
2018	J	`jnl`	Iterative Filtering and Smoothing in Nonlinear and Non-Gaussian Systems Using Conditional Moments. IEEE Signal Process. Lett. Filip Tronarp, Ángel F. García-Fernández, Simo Särkkä
2018	—	`conf`	Mixture Representation of the MatéRn class with Applications in State Space Approximations and Bayesian quadrature. MLSP Filip Tronarp, Toni Karvonen, Simo Särkkä
2018	C	`conf`	Non-Linear Continuous-Discrete Smoothing by Basis Function Expansions of Brownian Motion. FUSION Filip Tronarp, Simo Särkkä
2018	—	`conf`	Tracking of dynamic functional connectivity from MEG data with Kalman filtering. EMBC Filip Tronarp, Narayan Puthanmadam Subramaniyam, Simo Särkkä, Lauri Parkkonen
2017	C	`conf`	Student-t process quadratures for filtering of non-linear systems with heavy-tailed noise. FUSION Jakub Prüher, Filip Tronarp, Toni Karvonen, Simo Särkkä, Ondrej Straka
2016	C	`conf`	Sigma-point filtering for nonlinear systems with non-additive heavy-tailed noise. FUSION Filip Tronarp, Roland Hostettler, Simo Särkkä