4 citations · 4 across the 2 of their papers we have counts for
3 papers
Improve Convolutional Neural Network Pruning by Maximizing Filter Variety
Nathan Hubens, Matei Mancas, Bernard Gosselin +2
Neural network pruning is a widely used strategy for reducing model storage and computing requirements. It allows to lower the complexity of the network by introducing sparsity in…
End-to-end deep meta modelling to calibrate and optimize energy consumption and comfort
Max Cohen, Sylvain Le Corff, Maurice Charbit +2
In this paper, we propose a new end-to-end methodology to optimize the energy performance as well as comfort and air quality in large buildings without any renovation work. We intr…
End-to-end deep metamodeling to calibrate and optimize energy loads
Max Cohen, Maurice Charbit, Sylvain Le Corff +2
In this paper, we propose a new end-to-end methodology to optimize the energy performance and the comfort, air quality and hygiene of large buildings. A metamodel based on a Transf…