| Bayesian deep learning based method for probabilistic forecast of day-ahead electricity prices A Brusaferri, M Matteucci, P Portolani, A Vitali Applied Energy 250, 1158-1175, 2019 | 119 | 2019 |
| Probabilistic electric load forecasting through Bayesian mixture density networks A Brusaferri, M Matteucci, S Spinelli, A Vitali Applied Energy 309, 118341, 2022 | 37 | 2022 |
| Learning behavioral models by recurrent neural networks with discrete latent representations with application to a flexible industrial conveyor A Brusaferri, M Matteucci, S Spinelli, A Vitali Computers in Industry 122, 103263, 2020 | 10 | 2020 |
| Probabilistic day-ahead energy price forecast by a Mixture Density Recurrent Neural Network A Brusaferri, M Matteucci, D Ramin, S Spinelli, A Vitali 2020 7th International Conference on Control, Decision and Information …, 2020 | 10 | 2020 |
| Electricity technological mix forecasting for life cycle assessment aware scheduling S Cornago, A Vitali, C Brondi, JSC Low Procedia CIRP 90, 268-273, 2020 | 9 | 2020 |
| Day ahead electricity price forecast by narx model with lasso based features selection A Brusaferri, L Fagiano, M Matteucci, A Vitali 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) 1 …, 2019 | 9 | 2019 |
| Machine learning to forecast electricity hourly LCA impacts due to a dynamic electricity technology mix P Portolani, A Vitali, S Cornago, D Rovelli, C Brondi, JSC Low, ... Frontiers in Sustainability 3, 1037497, 2022 | 7 | 2022 |
| Hybrid system identification using a mixture of NARX experts with LASSO-based feature selection A Brusaferri, M Matteucci, P Portolani, S Spinelli, A Vitali 2020 7th International Conference on Control, Decision and Information …, 2020 | 7 | 2020 |
| Extracting finite state representations from recurrent models of Industrial Cyber Physical Systems A Brusaferri, M Matteucci, S Spinelli, A Vitali 2020 7th International Conference on Control, Decision and Information …, 2020 | | 2020 |
