Standard Error Estimation in Neural Network Regression Models: the AR-Sieve Bootstrap Approach. - Francesco Giordano; Michele La Rocca 001; Cira Perna (WIRN, 2001)

Neural Network Modeling by Subsampling. - Michele La Rocca 001; Cira Perna (IWANN, 2005)

Variable selection in neural network regression models with dependent data: a subsampling approach. - Michele La Rocca 001; Cira Perna (Comput. Stat. Data Anal., 2005)

Forecasting nonlinear time series with neural network sieve bootstrap. - Francesco Giordano; Michele La Rocca 001; Cira Perna (Comput. Stat. Data Anal., 2007)

A multiple testing procedure for input variable selection in neural networks. - Michele La Rocca 001; Cira Perna (ESANN, 2008)

Neural Network Sieve Bootstrap Prediction Intervals: Some Real Data Evidence. - Francesco Giordano; Michele La Rocca 001; Cira Perna (WIRN, 2008)

Testing the Weak Form Market Efficiency: Empirical Evidence from the Italian Stock Exchange. - Giuseppina Albano; Michele La Rocca 001; Cira Perna (WIRN, 2012)

Non Linear Time Series Analysis of Air Pollutants with Missing Data. - Giuseppina Albano; Michele La Rocca 001; Cira Perna (Advances in Neural Networks, 2016)

On the Imputation of Missing Values in Univariate PM_10 P M 10 Time Series. - Giuseppina Albano; Michele La Rocca 001; Cira Perna (EUROCAST (2), 2017)

Clustering complex time-series databases by using periodic components. - Francesco Giordano; Michele La Rocca 001; Maria Lucia Parrella (Stat. Anal. Data Min., 2017)

Volatility Modelling for Air Pollution Time Series. - Giuseppina Albano; Michele La Rocca 001; Cira Perna (EUROCAST (1), 2019)

Bootstrap joint prediction regions for sequences of missing values in spatio-temporal datasets. - Maria Lucia Parrella; Giuseppina Albano; Cira Perna; Michele La Rocca 001 (Comput. Stat., 2021)

Clustering nonlinear time series with neural network bootstrap forecast distributions. - Michele La Rocca 001; Francesco Giordano; Cira Perna (Int. J. Approx. Reason., 2021)

Deep learning for volatility forecasting in asset management. - Alessio Petrozziello; Luigi Troiano; Angela Serra; Ivan Jordanov; Giuseppe Storti; Roberto Tagliaferri; Michele La Rocca 001 (Soft Comput., 2022)

Technological Strategies and Quality of Invention: The Role of Knowledge Base and Technical Applications. - Antonello Cammarano; Francesca Michelino; Maria Prosperina Vitale; Michele La Rocca 001; Mauro Caputo (IEEE Trans. Engineering Management, 2022)

Neural Network Bootstrap Forecast Distributions with Extreme Learning Machines. - Michele La Rocca 001; Cira Perna (EANN, 2023)

Evaluating Forecast Distributions in Neural Network HAR-Type Models for Range-Based Volatility. - Michele La Rocca 001; Cira Perna (EANN, 2024)

Bootstrapping binary GEV regressions for imbalanced datasets. - Michele La Rocca 001; Marcella Niglio; Marialuisa Restaino (Comput. Stat., 2024)

Correction to: Bootstrapping binary GEV regressions for imbalanced datasets. - Michele La Rocca 001; Marcella Niglio; Marialuisa Restaino (Comput. Stat., 2024)

Effective signal reconstruction from multiple ranked lists via convex optimization. - Michael G. Schimek; Luca Vitale; Bastian Pfeifer; Michele La Rocca 001 (Data Min. Knowl. Discov., 2024)

Correction to: Effective signal reconstruction from multiple ranked lists via convex optimization. - Michael G. Schimek; Luca Vitale; Bastian Pfeifer; Michele La Rocca 001 (Data Min. Knowl. Discov., 2024)

Automatic Long-Term Forecasting of Mortality Rates with Generalized Regression Neural Networks. - Giovanna Apicella; Michele La Rocca 001; Cira Perna; Marilena Sibillo (EANN (2), 2025)