Dissecting Deep Neural Networks. - Haakon Robinson; Adil Rasheed; Omer San (CoRR, 2019)

Taming an Autonomous Surface Vehicle for Path Following and Collision Avoidance Using Deep Reinforcement Learning. - Eivind Meyer; Haakon Robinson; Adil Rasheed; Omer San (IEEE Access, 2020)

Safe Learning for Control using Control Lyapunov Functions and Control Barrier Functions: A Review. - Akhil S. Anand; Katrine Seel; Vilde B. Gjærum; Anne Håkansson; Haakon Robinson; Aya Saad (KES, 2021)

Robust Reasoning for Autonomous Cyber-Physical Systems in Dynamic Environments. - Anne Håkansson; Aya Saad; Akhil S. Anand; Vilde B. Gjærum; Haakon Robinson; Katrine Seel (KES, 2021)

A novel corrective-source term approach to modeling unknown physics in aluminum extraction process. - Haakon Robinson; Erlend Lundby; Adil Rasheed; Jan Tommy Gravdahl (CoRR, 2022)

Physics guided neural networks for modelling of non-linear dynamics. - Haakon Robinson; Suraj Pawar; Adil Rasheed; Omer San (Neural Networks, 2022)

Sparse Neural Networks with Skip-Connections for Identification of Aluminum Electrolysis Cell. - Erlend Torje Berg Lundby; Haakon Robinson; Adil Rasheed; Ivar Johan Halvorsen; Jan Tommy Gravdahl (CDC, 2023)

Sparse neural networks with skip-connections for nonlinear system identification. - Erlend Torje Berg Lundby; Haakon Robinson; Adil Rasheed; Ivar Johan Halvorsen; Jan Tommy Gravdahl (CoRR, 2023)

Deep learning assisted physics-based modeling of aluminum extraction process. - Haakon Robinson; Erlend Lundby; Adil Rasheed; Jan Tommy Gravdahl (Eng. Appl. Artif. Intell., 2023)

Trustworthy Machine Learning for Controlled Dynamic Systems. - Haakon Robinson (2023)