Sparse neural networks with skip-connections for identification of aluminum electrolysis cell

2 January 2023

Papers citing "Sparse neural networks with skip-connections for identification of aluminum electrolysis cell"

4 / 4 papers shown

Title
Explainable Bayesian deep learning through input-skip Latent Binary Bayesian Neural Networks Eirik Høyheim Lars Skaaret-Lund Solve Sæbø A. Hubin UQCV BDL 55 0 0 13 Mar 2025
A novel corrective-source term approach to modeling unknown physics in aluminum extraction process Haakon Robinson E. Lundby Adil Rasheed J. Gravdahl 20 5 0 22 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 139 684 0 31 Jan 2021
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 249 36,362 0 25 Aug 2016