| Short-series Prediction with BEMA Approach: application to short rainfall series CR Rivero, JA Pucheta, JS Baumgartner, SO Laboret, VH Sauchelli, ... IEEE Latin America Transactions 14 (8), 3892-3899, 2016 | 12 | 2016 |
| Noisy Chaotic time series forecast approximated by combining Reny's entropy with Energy associated to series method: application to rainfall series CR Rivero, J Pucheta, AO Canon, L Franco, YT Valdivia, P Otano, ... IEEE Latin America Transactions 15 (7), 1318-1325, 2017 | 8 | 2017 |
| Time series forecasting using recurrent neural networks modified by bayesian inference in the learning process CR Rivero, J Pucheta, P Otaño, AD Orjuela-Cañon, D Patiño, L Franco, ... 2019 IEEE Colombian Conference on Applications in Computational Intelligence …, 2019 | 6 | 2019 |
| Time-series prediction with BEMCA approach: Application to short rainfall series CR Rivero, Y Tupac, J Pucheta, G Juarez, L Franco, P Otaño 2017 IEEE Latin American Conference on Computational Intelligence (LA-CCI), 1-6, 2017 | 5 | 2017 |
| Bayesian enhanced ensemble approach (BEEA) for time series forecasting CR Rivero, J Pucheta, P Otaño, G Juárez, L Franco, D Patiño, R Velazco 2018 IEEE Biennial Congress of Argentina (ARGENCON), 1-7, 2018 | 4 | 2018 |
| Bayesian inference for training of long short term memory models in chaotic time series forecasting CR Rivero, J Pucheta, D Patiño, JL Puglisi, P Otaño, L Franco, G Juarez, ... Applications of Computational Intelligence: Second IEEE Colombian Conference …, 2019 | 2 | 2019 |
| Short-Term Rainfall Forecasting with E-LSTM Recurrent Neural Networks Using Small Datasets CR Rivero, J Pucheta, D Patiño, P Otaño, L Franco, G Juarez Intelligent Computing Methodologies: 16th International Conference, ICIC …, 2020 | 1 | 2020 |
| Time Series Forecasting using Recurrent Neural Networks modified by Bayesian Inference in the Learning Process C Rodriguez Rivero, J Pucheta, P Otaño, AD Orjuela-Cañon, D Patiño, ... Piscataway, NJIEEE, 2019 | | 2019 |
| Bayesian Inference for Training of Long Short Term Memory Models in Chaotic Time Series Forecasting C Rodríguez Rivero, J Pucheta, D Patiño, JL Puglisi, P Otaño, L Franco, ... ChamSpringer, 2019 | | 2019 |
| Time-series prediction with BEMCA approach: Application to short rainfall series C Rodriguez Rivero, YJ Túpac Valdivia, J Pucheta, G Juarez, L Franco, ... Institute of Electrical and Electronics Engineers Inc., 2018 | | 2018 |
| On predicting wind power series by using Bayesian Enhanced modified based-neural network CR Rivero, J Pucheta, P Otano, YT Valdivia, E Gorrostieta, S Laboret 2017 XVII Workshop on Information Processing and Control (RPIC), 1-6, 2017 | | 2017 |
| Noisy Chaotic time series forecast approximated by combining Reny's entropy with Energy associated to series method: Application to rainfall series A Orjuela Canon, V Sauchelli, J Pucheta, C Rodriguez Rivero, L Franco, ... IEEE Computer Society, 2017 | | 2017 |
| On predicting wind power series by using Bayesian Enhanced modified based-neural network C Rodriguez Rivero, J Pucheta, P Otano, YJ Túpac Valdivia, E Gorrostieta, ... Institute of Electrical and Electronics Engineers Inc., 2017 | | 2017 |
| Forecasting noisy time series approximated by neural networks C Rodríguez Rivero, J Pucheta, J Baumgartner, HD Patiño, S Laboret, ... | | |
| Ensemble Forecasting by Energy associated modified by Renyi’s entropy and statistical roughness in the learning process CR Rivero, J Pucheta, M Herrera, D Patiño, P Otaño, L Franco, G Juarez | | |
Cristian Rodriguez RiveroLecturer in Data Science - University of AmsterdamDirección de correo verificada de uva.nl
