Fusion framework and multimodality for the Laplacian approximation of Bayesian neural networks
M Malmström, I Skog, D Axehill… - arXiv preprint arXiv …, 2023 - arxiv.org
This paper considers the problem of sequential fusion of predictions from neural networks
(NN) and fusion of predictions from multiple NN. This fusion strategy increases the …
(NN) and fusion of predictions from multiple NN. This fusion strategy increases the …
[HTML][HTML] Uncertainty quantification in neural network classifiers—A local linear approach
Classifiers based on neural networks (nn) often lack a measure of uncertainty in the
predicted class. We propose a method to estimate the probability mass function (pmf) of the …
predicted class. We propose a method to estimate the probability mass function (pmf) of the …
Approximative Uncertainty in Neural Network Predictions
M Malmström - 2023 - diva-portal.org
Suppose data-driven black-box models, eg, neural networks, should be used as
components in safety-critical systems such as autonomous vehicles. In that case, knowing …
components in safety-critical systems such as autonomous vehicles. In that case, knowing …