2 papers
cs.LG2019
Efficient Per-Example Gradient Computations in Convolutional Neural Networks
Gaspar Rochette, Andre Manoel, Eric W. Tramel
Deep learning frameworks leverage GPUs to perform massively-parallel computations over batches of many training examples efficiently. However, for certain tasks, one may be interes…
eess.SP2018
Phase Harmonic Correlations and Convolutional Neural Networks
Stéphane Mallat, Sixin Zhang, Gaspar Rochette
A major issue in harmonic analysis is to capture the phase dependence of frequency representations, which carries important signal properties. It seems that convolutional neural ne…