A novel corrective-source term approach to modeling unknown physics in aluminum extraction process

22 September 2022

Papers citing "A novel corrective-source term approach to modeling unknown physics in aluminum extraction process"

5 / 5 papers shown

Title
Sparse neural networks with skip-connections for identification of aluminum electrolysis cell E. Lundby Haakon Robinson Adil Rasheed I. Halvorsen J. Gravdahl 30 2 0 02 Jan 2023
Artificial intelligence-driven digital twin of a modern house demonstrated in virtual reality Elias Mohammed Elfarri Adil Rasheed Omer San 29 16 0 14 Dec 2022
Sparse deep neural networks for modeling aluminum electrolysis dynamics E. Lundby Adil Rasheed I. Halvorsen J. Gravdahl 26 14 0 13 Sep 2022
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 141 684 0 31 Jan 2021
Physics guided machine learning using simplified theories Suraj Pawar Omer San Burak Aksoylu Adil Rasheed T. Kvamsdal PINN AI4CE 105 106 0 18 Dec 2020