| 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 | 18 | 2021 |
| 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 | 6 | 2021 |
| 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 | 6 | 2020 |
| Iterated Filters for Nonlinear Transition Models A Kullberg, I Skog, G Hendeby 2023 26th International Conference on Information Fusion (FUSION), 1-8, 2023 | 2 | 2023 |
| 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 | 1 | 2024 |
| 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 | | 2023 |
| 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 |
| 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 | | 2023 |
| On Joint State Estimation and Model Learning Using Gaussian Process Approximations A Kullberg Linköping University Electronic Press, 2021 | | 2021 |
Isaac SkogLinköping UniversityVerifierad e-postadress på liu.se
