Search Results for author: Fernando Fernandes Neto

Found 3 papers, 0 papers with code

Deep Haar Scattering Networks in Pattern Recognition: A promising approach

no code implementations29 Nov 2018 Fernando Fernandes Neto, Alemayehu Admasu Solomon, Rodrigo de Losso, Claudio Garcia, Pedro Delano Cavalcanti

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 few parameters, in a relatively broad set of pattern recognition problems, including regression and classification tasks.

Classification General Classification +3

Building Function Approximators on top of Haar Scattering Networks

no code implementations9 Apr 2018 Fernando Fernandes Neto

In this article we propose building general-purpose function approximators on top of Haar Scattering Networks.

Econometrics

Generative Models for Stochastic Processes Using Convolutional Neural Networks

no code implementations9 Jan 2018 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 (such as quantitative finance and physics) to develop a general tool for forecasts and simulations without the need to identify/assume a specific system structure or estimate its parameters.

Cannot find the paper you are looking for? You can Submit a new open access paper.