3 papers
eess.SP2018
Deep Haar Scattering Networks in Pattern Recognition: A promising approach
Fernando Fernandes Neto, Alemayehu Admasu Solomon, Rodrigo de Losso +2
The aim of this paper is to discuss the use of Haar scattering networks, which is a very simple architecture that naturally supports a large number of stacked layers, yet with very…
stat.ML2018
Building Function Approximators on top of Haar Scattering Networks
Fernando Fernandes Neto
In this article we propose building general-purpose function approximators on top of Haar Scattering Networks. We advocate that this architecture enables a better comprehension of…
stat.ML2018
Generative Models for Stochastic Processes Using Convolutional Neural Networks
Fernando Fernandes Neto
The present paper aims to demonstrate the usage of Convolutional Neural Networks as a generative model for stochastic processes, enabling researchers from a wide range of fields (s…