Go with the Flow: Recurrent Networks for Wind Time Series Multi-Step Forecasting. - Jaume Manero; Javier Béjar; Ulises Cortés (CCIA, 2018)

Predicting Wind Energy Generation with Recurrent Neural Networks. - Jaume Manero; Javier Béjar; Ulises Cortés (IDEAL (1), 2018)

Wind Energy Forecasting with Neural Networks: A Literature Review. - Jaume Manero; Javier Béjar; Ulises Cortés (Computación y Sistemas, 2018)

Deep learning architectures applied to wind time series multi-step forecasting. - Jaume Manero Font (2020)

Wind Prediction Using Deep Learning and High Performance Computing. - Jaume Manero; Javier Béjar; Ulises Cortés (CARLA, 2021)

Forecastability Measures that Describe the Complexity of a Site for Deep Learning Wind Predictions. - Jaume Manero; Javier Béjar (Supercomput. Front. Innov., 2021)

Intrusion Detection in SCADA Based Power Grids: Recursive Feature Elimination Model With Majority Vote Ensemble Algorithm. - Darshana Upadhyay; Jaume Manero; Marzia Zaman; Srinivas Sampalli (IEEE Trans. Netw. Sci. Eng., 2021)

Gradient Boosting Feature Selection With Machine Learning Classifiers for Intrusion Detection on Power Grids. - Darshana Upadhyay; Jaume Manero; Marzia Zaman; Srinivas Sampalli (IEEE Trans. Netw. Serv. Manag., 2021)

Comparative Analysis of Tabular Generative Adversarial Network (GAN) Models for Generation and Validation of Power Grid Synthetic Datasets. - Darshana Upadhyay; Qiaodan Luo; Jaume Manero; Marzia Zaman; Srinivas Sampalli (EUROCON, 2023)

IoT-Enabled Pediatric Pain Care Leveraging Majority Vote-Based Transfer Learning Models. - Nupur Gaikwad; Darshana Upadhyay; Jaume Manero; Srinivas Sampalli (CIoT, 2024)