Safe learning for control using control lyapunov functions and control barrier functions: A review A Anand, K Seel, V Gjærum, A Håkansson, H Robinson, A Saad Procedia Computer Science 192, 3987-3997, 2021 | 21 | 2021 |
Explaining a deep reinforcement learning docking agent using linear model trees with user adapted visualization VB Gjærum, I Strümke, OA Alsos, AM Lekkas Journal of Marine Science and Engineering 9 (11), 1178, 2021 | 17 | 2021 |
Model tree methods for explaining deep reinforcement learning agents in real-time robotic applications VB Gjærum, I Strümke, J Løver, T Miller, AM Lekkas Neurocomputing 515, 133-144, 2023 | 15 | 2023 |
Explainable AI methods on a deep reinforcement learning agent for automatic docking J Løver, VB Gjærum, AM Lekkas IFAC-PapersOnLine 54 (16), 146-152, 2021 | 12 | 2021 |
Approximating a deep reinforcement learning docking agent using linear model trees VB Gjærum, ELH Rørvik, AM Lekkas 2021 European Control Conference (ECC), 1465-1471, 2021 | 9 | 2021 |
Robust reasoning for autonomous cyber-physical systems in dynamic environments A Håkansson, A Saad, A Anand, V Gjærum, H Robinson, K Seel Procedia Computer Science 192, 3966-3978, 2021 | 7 | 2021 |
Real-Time Counterfactual Explanations For Robotic Systems With Multiple Continuous Outputs VB Gjærum, I Strümke, AM Lekkas, T Miller IFAC-PapersOnLine 56 (2), 7-12, 2023 | 2 | 2023 |
Machine learning in robotics: Explaining autonomous agents in real time VB Gjærum NTNU, 2023 | | 2023 |
A Novel Approach to Autonomous Human Safe UAVs for Man-Machine Interaction and Cooperation VB Gjærum, PMW Teigmo, VA Bergum, H Fauskanger | | 2019 |
Autonomous navigation along power lines using monocular camera VB Gjærum NTNU, 2019 | | 2019 |