Blar i Fakultet for informasjonsteknologi og elektroteknikk (IE) på tidsskrift "Neural Networks"
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Deep neural network enabled corrective source term approach to hybrid analysis and modeling
(Peer reviewed; Journal article, 2022)In this work, we introduce, justify and demonstrate the Corrective Source Term Approach (CoSTA)—a novel approach to Hybrid Analysis and Modeling (HAM). The objective of HAM is to combine physics-based modeling (PBM) and ... -
Echo State Networks for data-driven downhole pressure estimation in gas-lift oil wells
(Journal article; Peer reviewed, 2017)Process measurements are of vital importance for monitoring and control of industrial plants. When we consider offshore oil production platforms, wells that require gas-lift technology to yield oil production from low ... -
Physics guided neural networks for modelling of non-linear dynamics
(Peer reviewed; Journal article, 2022)The success of the current wave of artificial intelligence can be partly attributed to deep neural networks, which have proven to be very effective in learning complex patterns from large datasets with minimal human ... -
Risk-based implementation of COLREGs for autonomous surface vehicles using deep reinforcement learning
(Peer reviewed; Journal article, 2022)Autonomous systems are becoming ubiquitous and gaining momentum within the marine sector. Since the electrification of transport is happening simultaneously, autonomous marine vessels can reduce environmental impact, lower ... -
Sparse factorization of square matrices with application to neural attention modeling
(Peer reviewed; Journal article, 2022)Square matrices appear in many machine learning problems and models. Optimization over a large square matrix is expensive in memory and in time. Therefore an economic approximation is needed. Conventional approximation ...