18 citations · 20 across the 4 of their papers we have counts for
4 papers
Deep active learning for nonlinear system identification
Erlend Torje Berg Lundby, Adil Rasheed, Ivar Johan Halvorsen +3
The exploding research interest for neural networks in modeling nonlinear dynamical systems is largely explained by the networks' capacity to model complex input-output relations d…
Sparse neural networks with skip-connections for identification of aluminum electrolysis cell
Erlend Torje Berg Lundby, Haakon Robinsson, Adil Rasheed +2
Neural networks are rapidly gaining interest in nonlinear system identification due to the model's ability to capture complex input-output relations directly from data. However, de…
A novel corrective-source term approach to modeling unknown physics in aluminum extraction process
Haakon Robinson, Erlend Lundby, Adil Rasheed +1
With the ever-increasing availability of data, there has been an explosion of interest in applying modern machine learning methods to fields such as modeling and control. However,…
Sparse deep neural networks for modeling aluminum electrolysis dynamics
Erlend Torje Berg Lundby, Adil Rasheed, Ivar Johan Halvorsen +1
Deep neural networks have become very popular in modeling complex nonlinear processes due to their extraordinary ability to fit arbitrary nonlinear functions from data with minimal…