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Anton Kullberg
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Online Joint State Inference and Learning of Partially Unknown State-Space Models
A Kullberg, I Skog, G Hendeby
IEEE Transactions on Signal Processing 69, 4149-4161, 2021
192021
Learning motion patterns in AIS data and detecting anomalous vessel behavior
A Kullberg, I Skog, G Hendeby
2021 IEEE 24th International conference on information fusion (FUSION), 1-8, 2021
82021
Learning driver behaviors using a Gaussian process augmented state-space model
A Kullberg, I Skog, G Hendeby
2020 IEEE 23rd International Conference on Information Fusion (FUSION), 1-7, 2020
72020
Iterated Filters for Nonlinear Transition Models
A Kullberg, I Skog, G Hendeby
2023 26th International Conference on Information Fusion (FUSION), 1-8, 2023
42023
Extended target tracking utilizing machine-learning software–with applications to animal classification
M Malmström, A Kullberg, I Skog, D Axehill, F Gustafsson
IEEE Signal Processing Letters, 2024
22024
On the Relationship Between Iterated Statistical Linearization and Quasi–Newton Methods
A Kullberg, MA Skoglund, I Skog, G Hendeby
IEEE Signal Processing Letters 30, 1777-1781, 2023
22023
Dynamically Iterated Filters: A unified framework for improved iterated filtering and smoothing
A Kullberg, MA Skoglund, I Skog, G Hendeby
arXiv preprint arXiv:2404.15359, 2024
12024
Fast or Cheap: Time and Energy Optimal Control of Ship-to-Shore Cranes
FM Barbosa, A Kullberg, J Löfberg
IFAC-PapersOnLine 56 (2), 3126-3131, 2023
12023
On Joint State Estimation and Model Learning Using Gaussian Process Approximations
A Kullberg
Linköping University Electronic Press, 2021
12021
Dynamic rEvolution: Adaptive state estimation via Gaussian processes and iterative filtering
A Kullberg
Linköping University Electronic Press, 2024
2024
Unified Linearization-based Nonlinear Filtering
A Kullberg, I Skog, G Hendeby
arXiv preprint arXiv:2309.07631, 2023
2023
Fast or Cheap: Time and Energy Optimal Control of Ship-to-Shore Cranes
F Marques Barbosa, A Kullberg, J Löfberg
arXiv e-prints, arXiv: 2304.09232, 2023
2023
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