On the Expressive Power of Deep Fully Circulant Neural Networks

We provide a large probability bound on the uniform approximation of fractional Brownian motion with Hurst parameter H , by a deep-feedforward ReLU neural network fed with a

Based on the analysis of the cathodic polarization curve, HAp coating was electrodeposited in the electrolyte solution (pH=4.4) with different scanning potential ranges: from 0

The design capitalizes on the prominent location of the Kneeland Street edge as a potential "gateway" into Chinatown, and pro- poses to create on this highly visible

We investigate deep Bayesian neural net- works with Gaussian priors on the weights and ReLU-like nonlinearities, shedding light on novel sparsity-inducing mechanisms at the level of

In our previous paper [7] we have shown that the theory of circulant ma- trices allows to recover the result that there exists p + 1 Mutually Unbiased Bases in dimension p, p being

Finally, we construct a family of pairs of generalized circulant graphs, with the same number of nodes and links, but with different clustering coefficients.. Keywords:

Even though our CPU is quite powerful, running the back-propagation algorithm took a long time (approximately 20 minutes to compute the feature importances for a 4 hidden layers

Example of input signals and outputs after applying the reconstruction techniques (a) Input signal; (b) Output signal using Bayesian technique combined with Circulant matrix;