Guenther Schwedersky Neto

According to our database, Guenther Schwedersky Neto authored at least 9 papers between 2009 and 2017.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2017

Hybrid Global Stochastic and Bayesian Linearized Acoustic Seismic Inversion Methodology.

Fernando Luis Bordignon, Leandro Passos de Figueiredo, Leonardo Azevedo, Amílcar Soares, Mauro Roisenberg, Guenther Schwedersky Neto

IEEE Trans. Geosci. Remote. Sens., 2017

Bayesian seismic inversion based on rock-physics prior modeling for the joint estimation of acoustic impedance, porosity and lithofacies.

Leandro Passos de Figueiredo, Dario Grana, Marcio Santos, Wagner Figueiredo, Mauro Roisenberg, Guenther Schwedersky Neto

J. Comput. Phys., 2017

2016

Improving the Incremental Gaussian Mixture Neural Network model for spatial interpolation and geostatistical simulation.

Sérgio Aurélio Ferreira Soares, Guenther Schwedersky Neto, Mauro Roisenberg

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

2014

Bayesian Framework to Wavelet Estimation and Linearized Acoustic Inversion.

Leandro Passos de Figueiredo, Marcio Santos, Mauro Roisenberg, Guenther Schwedersky Neto, Wagner Figueiredo

IEEE Geosci. Remote. Sens. Lett., 2014

A topological niching covariance matrix adaptation for multimodal optimization.

Marcio Weck Pereira, Guenther Schwedersky Neto, Mauro Roisenberg

Proceedings of the IEEE Congress on Evolutionary Computation, 2014

2013

Fast Seismic Inversion Methods Using Ant Colony Optimization Algorithm.

Cassio Rodrigo Conti, Mauro Roisenberg, Guenther Schwedersky Neto, Milton José Porsani

IEEE Geosci. Remote. Sens. Lett., 2013

2012

ACOℝ-V - An algorithm that incorporates the visibility heuristic to the ACO in continuous domain.

Cassio Rodrigo Conti, Mauro Roisenberg, Guenther Schwedersky Neto

Proceedings of the IEEE Congress on Evolutionary Computation, 2012

2010

Efficient Confidence Bounds for RBF Networks for Sparse and High Dimensional Data.

Abner Rodrigues Neto, Mauro Roisenberg, Guenther Schwedersky Neto

Proceedings of the Artificial Neural Networks - ICANN 2010, 2010

2009

A method to estimate prediction intervals for artificial neural networks that is sensitive to the noise distribution in the outputs.

Cicero A. M. da Silva Neves, Mauro Roisenberg, Guenther Schwedersky Neto

Proceedings of the International Joint Conference on Neural Networks, 2009