Haakon Robinson

According to our database, Haakon Robinson authored at least 10 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Trustworthy Machine Learning for Controlled Dynamic Systems.

Haakon Robinson

PhD thesis, 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

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

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

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

Physics guided neural networks for modelling of non-linear dynamics.

Haakon Robinson, Suraj Pawar, Adil Rasheed, Omer San

Neural Networks, 2022

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

2021

Robust Reasoning for Autonomous Cyber-Physical Systems in Dynamic Environments.

Anne Håkansson, Aya Saad, Akhil Anand, Vilde B. Gjærum, Haakon Robinson, Katrine Seel

Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 25th International Conference KES-2021, 2021

Safe Learning for Control using Control Lyapunov Functions and Control Barrier Functions: A Review.

Akhil Anand, Katrine Seel, Vilde B. Gjærum, Anne Håkansson, Haakon Robinson, Aya Saad

Proceedings of the Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 25th International Conference KES-2021, 2021

2020

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

2019

Dissecting Deep Neural Networks.

Haakon Robinson, Adil Rasheed, Omer San

CoRR, 2019