| A dimensionality reduction approach for convolutional neural networks L Meneghetti, N Demo, G Rozza Applied Intelligence 53 (19), 22818-22833, 2023 | 12 | 2023 |
| A continuous convolutional trainable filter for modelling unstructured data D Coscia, L Meneghetti, N Demo, G Stabile, G Rozza Computational Mechanics 72 (2), 253-265, 2023 | 8 | 2023 |
| A Proper Orthogonal Decomposition approach for parameters reduction of Single Shot Detector networks L Meneghetti, N Demo, G Rozza 2022 IEEE International Conference on Image Processing (ICIP), 2206-2210, 2022 | 3 | 2022 |
| Chapter 20: A Deep Learning Approach to Improving Reduced Order Models L Meneghetti, N Shah, M Girfoglio, N Demo, M Tezzele, A Lario, G Stabile, ... Advanced Reduced Order Methods and Applications in Computational Fluid …, 2022 | 1 | 2022 |
| A continuous trainable filter for convolution with unstructured data D Coscia, L Meneghetti, N Demo, G Stabile, G Rozza | 1 | 2022 |
| Towards a continuous dynamic model of the Hopfield theory on neuronal interaction and memory storage L Meneghetti | 1 | 2018 |
| New Research topics: examples of new projects in the group L Meneghetti, N Demo, G Stabile, M Teruzzi, G Rozza | | 2022 |
| A Reduced Order Approach for Artificial Neural Networks applied to Object Recognition L Meneghetti SISSA, 2022 | | 2022 |
| Reduced Convolutional Neural Networks for image recognition in professional appliances L Meneghetti, N Demo, G Rozza PROCEEDINGS OF SIMAI 2020+ 21, 2021 | | 2021 |
| Towards a continuous dynamic model of the Hopfield theory on neuronal interaction and memory storage F Cardin, L Meneghetti | | 2018 |
| Convolutional Neural Networks for object detection in professional appliances L Meneghetti, N Demo, G Rozza, M Sonego | | |
