Publications
- Approximative Uncertainty in Neural Network Predictions, Magnus Malmström, Ph.D Thesis , 2023
- Extended target tracking utilizing machine-learning software–with applications to animal classification Magnus Malmström, Anton Kullberg, Isaac Skog, Daniel Axehill, Fredrik Gustafsson, preprint, 2023
- Fusion framework and multimodality for the Laplacian approximation of Bayesian neural networks Magnus Malmström, Isaac Skog, Daniel Axehill, Fredrik Gustafsson, preprint, 2023.
- Uncertainty quantification in neural network classifiers – a local linear approach Magnus Malmström, Isaac Skog, Daniel Axehill, Fredrik Gustafsson, preprint, 2023.
- On the validity of using the delta method for calculating the uncertainty of the predictions from an overparameterized model Magnus Malmström, Isaac Skog, Daniel Axehill, Fredrik Gustafsson, Proc. of 22nd IFAC World Congress, (IFAC), 2023
- Detection of outliers in classification by using quantified uncertainty in neural networks Magnus Malmström, Isaac Skog, Daniel Axehill, Fredrik Gustafsson, Proc. of {IEEE} 25th Int. Conf. on Inf. Fusion (FUSION), 2022
- A Novel and Fast Approach for Reconstructing {CASSI}-Raman Spectra using Generative Adversarial Networks Jacob Eek, David Gustafsson, Ludwig Hollmann, , Markus Nordberg, Isaac Skog, Magnus Malmström, 11th Int. Conf. on Image Proc. Theory, Tools and App. (IPTA), 2022
- Modeling of the tire-road friction using neural networks including quantification of the prediction uncertainty Magnus Malmström, Isaac Skog, Daniel Axehill, Fredrik Gustafsson, Proc. of {IEEE} 24th Int. Conf. on Inf. Fusion (FUSION), 2021
- Uncertainties in Neural Networks A System Identification Approach Magnus Malmström, Licentiate Thesis , 2021
- Asymptotic Prediction Error Variance for Feedforward Neural Networks, Magnus Malmström, Isaac Skog, Daniel Axehill, Fredrik Gustafsson Proc. of 21st IFAC World Congress, (IFAC), 2020
- 5G Positioning - A Machine Learning Approach Magnus Malmström, Isaac Skog, Sara Modarres Razavi, Yuxin Zhao, Fredrik Gunnarsson, Proc. of {IEEE} 16th Workshop on Positioning Navig. Commun. , (WPNC) 2019
- 5G Positioning using Machine Learning Magnus Malmström, Master Thesis , 2018
Presentations
