Overview
My research interests lie at the intersection of deep learning and dynamical systems.
This typically includes topics related to scientific machine learning and data-driven dynamical systems, with applications like system identification, time-series modeling and optimal control.
I'm not affiliated with any research institution, so I'm currently working on a research project independently.
Peer Reviewed Papers
Work in progress
2025
Learning Ordinary Differential Equations with the Line Integral Loss Function
Albert Johannessen
2022
NeurIPS 2022 Workshop - The Symbiosis of Deep Learning and Differential Equations II
Master Theses
Modeling Dynamical Systems with Physics Informed Neural Networks with Applications to PDE-Constrained Optimal Control Problems
Albert Johannessen
2024
NTNU Open
Motion Classification with Neural Ordinary Differential Equations
Albert Johannessen
2022
NTNU Open

