153 citations · 899 across the 45 of their papers we have counts for
4 papers · 1 filter
Topology Reduction in Deep Convolutional Feature Extraction Networks
Thomas Wiatowski, Philipp Grohs, Helmut Bölcskei
Deep convolutional neural networks (CNNs) used in practice employ potentially hundreds of layers and ,s of nodes. Such network sizes entail significant computational compl…
Stable Gabor Phase Retrieval and Spectral Clustering
Philipp Grohs, Martin Rathmair
We consider the problem of reconstructing a signal from its spectrogram, i.e., the magnitudes of its Gabor transform $$V_φf (x,y):=\int_{\mathbb{R}}f(t)e^{-π(t-x)^2}e^…
Optimal Approximation with Sparsely Connected Deep Neural Networks
Helmut Bölcskei, Philipp Grohs, Gitta Kutyniok +1
We derive fundamental lower bounds on the connectivity and the memory requirements of deep neural networks guaranteeing uniform approximation rates for arbitrary function classes i…
Energy Propagation in Deep Convolutional Neural Networks
Thomas Wiatowski, Philipp Grohs, Helmut Bölcskei
Many practical machine learning tasks employ very deep convolutional neural networks. Such large depths pose formidable computational challenges in training and operating the netwo…