Publications

[W1] P. Pilar and N. Wahlström. Probabilistic Matching of Real and Generated Data Statistics in Generative Adversarial Networks Paper

[B1] A. Lindholm, N. Wahlström, F. Lindsten, and T. B. Schön. Machine Learning - A First Course for Engineers and Scientists. Cambridge University Press, 2022. Book

2023

[J9] Daniel Gedon, Antonio H. Ribeiro, Niklas Wahlström, and Thomas B. Schön.
Invertible kernel PCA with random fourier features. IEEE Signal Processing Letters,
30:563–567, 2023. Paper

2022

[J8] Philipp Pilar, C. Jidling, T. B. Schön, and N. Wahlström. Incorporating sum constraints into multitask Gaussian processes. Transactions on Machine Learning Research, 2022. Paper

2019

[J7] Z. Purisha, C. Jidling, N. Wahlström, T. Schön, and S. Särkkä. Probabilistic approach to limited-data computed tomography reconstruction. Inverse Problems, 2019. Paper

2018

[J6] C. Jidling, J. Hendriks, N. Wahlström, A. Gregg, T. B. Schön, C. Wensrich, and A. Wills. Probabilistic modelling and reconstruction of strain. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, 436:141 – 155, 2018, Paper

[J5] A. Solin, M. Kok, N. Wahlström, T. B. Schön, and S. Särkkä. Modeling and interpolation of the ambient magnetic field by Gaussian processes. IEEE Transactions on Robotics, 34(4):1112 – 1127, Paper

2017

[J4] G. Hendeby, F. Gustafsson, N. Wahlström, S. Gunnarsson, Platform for Teaching Sensor Fusion Using a Smartphone. International Journal of Engineering Education, 33(2B), pp 781-789, Paper

2015

[J3] N. Wahlström and E. Özkan, Extended Target Tracking Using Gaussian Processes. IEEE Transactions on Signal Processing. 63(16), pp 4165-4178 Paper

2014

[J2] N. Wahlström, R. Hostettler, F. Gustafsson and W. Birk, Classification of Driving Direction in Traffic Surveillance using Magnetometers. IEEE Transactions on Intelligent Transportation Systems. 15(4), pp 1405-1418 Paper

[J1] N. Wahlström and F. Gustafsson,
Magnetometer Modeling and Validation for Tracking Metallic Targets. IEEE Transactions on Signal Processing. 62(3), pp 545-556 Paper

2024

[C22] P. Pilar and N. Wahlström. Physics-informed neural networks with unknown measurement noise. Learning for Dynamics & Control Conference, Oxford, July 2024 (accepted). Also presented at NeurIPS 2023 workshop on Machine Learning and the Physical Sciences, New Orleans, US, December 2023. Paper

2021

[C21] D. Gedon, A. H. Ribeiro, N. Wahlström , and T. B. Schön. First steps towards self-supervised pretraining of the 12-lead ECG. In Proceedings of the 48th Computing in Cardiology Conference (CinC), Virtual conference, September 2021. Paper

[C20] C. Andersson, N. Wahlström, and T. B. Schön. Learning deep autoregressive models for hierarchical data. In 19th IFAC Symposium on System Identification (SYSID), Virtual conference, July 2021. Paper

[C19] D. Gedon, N. Wahlström, T. B. Schön, and L. Ljung. Deep state space models for nonlinear system identification. In 19th IFAC Symposium on System Identification (SYSID), Virtual conference, July 2021. Paper

2019

[C18] C. Andersson, A.H. Ribeiro, K. Tiels, N. Wahlström, and T. B. Schön. Deep convolutional networks in system identification. In Proceedings of the IEEE 58th Conference on Decision and Control (CDC), Nice, France, 2019. Paper

2018

[C17] C. Andersson, N. Wahlström, and T. B. Schön. Data-driven impulse response regularization via deep learning. In Proceedings of the 18th IFAC Symposium on System Identification (SYSID), Stockholm, Sweden, 2018. Paper

2017

[C16] C. Jidling, N. Wahlström, A. Wills, and T. B. Schön. Linearly constrained Gaussian processes. The Annual Conference on Neural Information Processing Systems (NIPS), Long Beach, CA, US, December 2017. Paper

2016

[C15] E. Özkan, N. Wahlström, and S. J. Godsill, Rao-Blackwellised particle filter for star-convex extended target tracking models. The 19th International Conference on Information Fusion (FUSION), Heidelberg, Germany, July 2016. paper

[C14] F. Ceragioli, G. Lindmark, C. Veibäck, N. Wahlström, M. Lindfors, and C. Altafini. A bounded confidence model that preserves the signs of the opinion. European Control Conference 2016. paper

[C13] J. A. Assael, N. Wahlström, T. B. Schön, and M. P. Deisenroth. Data-efficient learning of feedback policies from image pixels using deep dynamical models. Deep Reinforcement Learning Workshop at the Annual Conference on Neural Information Processing Systems (NIPS) . Paper

2015

[C12] N. Wahlström, T. B. Schön, M. P. Deisenroth, Learning deep dynamical models from image pixels.
The 17th IFAC Symposium on System Identification (SYSID). arXiv Slides

[C11] N. Wahlström, T. B. Schön, M. P. Deisenroth From Pixels to Torques: Policy Learning with Deep Dynamical Models. Deep learning Workshop at the International Conference on Machine Learning. Paper

2014

[C10] G. Hendeby, F. Gustafsson, and N. Wahlström, Teaching Sensor Fusion and Kalman Filtering using a Smartphone. The 19th World Congress of the International Federation of Automatic Control (IFAC), Cape Town, South Africa, August, 2014. Paper

[C9] N. Wahlström, P. Axelsson, and F. Gustafsson. Discretizing stochastic dynamical systems using Lyapunov equations. The 19th World Congress of the International Federation of Automatic Control (IFAC), Cape Town, South Africa, August, 2014. arXiv Slides Poster

[C8] V. Deleskog, H. Habberstad, G. Hendeby, D. Lindgren and N. Wahlström, Robust NLS Sensor Localization using MDS Initialization. The 17th International Conference on Information Fusion (FUSION), Salamanca, July, 2014. Paper

2013

[C7] N. Wahlström, M. Kok, T.B. Schön, and F. Gustafsson. Modeling Magnetic Fields using Gaussian Processes.
The 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vancouver, Canada, May, 2013. Paper Poster

[C6] M. Kok, N. Wahlström, T.B. Schön, and F. Gustafsson. MEMS-based inertial navigation based on a magnetic field map.. The 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vancouver, Canada, May, 2013. Paper

2012

[C5] N. Wahlström, F. Gustafsson and S. Åkesson, A Voyage to Africa by Mr Swift.
The 15th International Conference on Information Fusion (FUSION), Singapore, July, 2012. Paper Slides

[C4] N. Wahlström, R. Hostettler, F. Gustafsson and W. Birk, Rapid Classification of Vehicle Heading Direction with two-axis Magnetometer. The 37th International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, Japan, March, 2012. Paper Slides Poster

2011

[C3] N. Wahlström, J. Callmer and F. Gustafsson, Single Target Tracking using Vector Magnetometers.
The 36th International Conference on Acoustics, Speech and Signal Processing (ICASSP), Prague, Czech Republic,
May, 2011. Paper Poster

2010

[C2] N. Wahlström, J. Callmer and F. Gustafsson, Magnetometers for tracking metallic targets. The 13th International Conference on Information Fusion (FUSION), Edinburgh, UK, July, 2010. Paper

[C1] E. Almqvist, D. Eriksson, A. Lundberg, E. Nilsson, N. Wahlström, E. Frisk, and M. Krysander,Solving the ADAPT Benchmark Problem - A Student Project Study. 21st International Workshop on Principles of Diagnosis (DX-10). Portland, Oregon, USA. 2010 Paper

2013

[P1] F. Gustafsson, N.Wahlström, Method and Device for Pose Tracking Using Vector Magnetometers. US Patent (US 20130249784 A1) Patent

2015

[T3] N. Wahlström, Modeling of Magnetic Fields and Extended Objects for Localization Applications. PhD Thesis. Defended on December 4, 2015. Thesis

2013

[T2] N. Wahlström, Localization using Magnetometers and Light Sensors.
Licentiate's Thesis. Defended on March 13, 2013. Thesis Slides

2010

[T1] N. Wahlström, Target Tracking using Maxwell's Equations. Master's Thesis. Defended on June 15, 2010. Thesis