| Unveiling COVID-19 from Chest X-ray with deep learning: a hurdles race with small data E Tartaglione, CA Barbano, C Berzovini, M Calandri, M Grangetto Int. J. Environ. Res. Public Health 2020 17 (18), 6933, 2020 | 145 | 2020 |
| Learning sparse neural networks via sensitivity-driven regularization E Tartaglione, S Lepsøy, A Fiandrotti, G Francini Advances in Neural Information Processing Systems, 3878-3888, 2018 | 68 | 2018 |
| EnD: Entangling and Disentangling deep representations for bias correction E Tartaglione, CA Barbano, M Grangetto IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021), 2021 | 25 | 2021 |
| Role of synaptic stochasticity in training low-precision neural networks C Baldassi, F Gerace, HJ Kappen, C Lucibello, L Saglietti, E Tartaglione, ... Physical review letters 120 (26), 268103, 2018 | 22 | 2018 |
| Pruning artificial neural networks: A way to find well-generalizing, high-entropy sharp minima E Tartaglione, A Bragagnolo, M Grangetto International Conference on Artificial Neural Networks, 67-78, 2020 | 11 | 2020 |
| Take a ramble into solution spaces for classification problems in neural networks E Tartaglione, M Grangetto International conference on image analysis and processing, 345-355, 2019 | 7 | 2019 |
| Loss-based sensitivity regularization: towards deep sparse neural networks E Tartaglione, A Bragagnolo, A Fiandrotti, M Grangetto Neural Networks 146, 230-237, 2022 | 6 | 2022 |
| UniToPatho, a labeled histopathological dataset for colorectal polyps classification and adenoma dysplasia grading CA Barbano, D Perlo, E Tartaglione, A Fiandrotti, L Bertero, P Cassoni, ... 2021 IEEE International Conference on Image Processing (ICIP), 76-80, 2021 | 6 | 2021 |
| SeReNe: Sensitivity based Regularization of Neurons for Structured Sparsity in Neural Networks E Tartaglione, A Bragagnolo, F Odierna, A Fiandrotti, M Grangetto IEEE Transactions on Neural Networks and Learning Systems, 2021 | 6 | 2021 |
| Post-synaptic potential regularization has potential E Tartaglione, D Perlo, M Grangetto International Conference on Artificial Neural Networks, 187-200, 2019 | 5 | 2019 |
| HEMP: High-order entropy minimization for neural network compression E Tartaglione, S Lathuilière, A Fiandrotti, M Cagnazzo, M Grangetto Neurocomputing 461, 244-253, 2021 | 4 | 2021 |
| Applications of AI and HPC in the Health Domain D Oniga, B Cantalupo, E Tartaglione, D Perlo, M Grangetto, M Aldinucci, ... HPC, Big Data, and AI Convergence Towards Exascale, 217-239, 2022 | 3 | 2022 |
| Delving in the loss landscape to embed robust watermarks into neural networks E Tartaglione, M Grangetto, D Cavagnino, M Botta 2020 25th International Conference on Pattern Recognition (ICPR), 1243-1250, 2021 | 3 | 2021 |
| A non-discriminatory approach to ethical deep learning E Tartaglione, M Grangetto 2020 IEEE 19th International Conference on Trust, Security and Privacy in …, 2020 | 3 | 2020 |
| On the role of structured pruning for neural network compression A Bragagnolo, E Tartaglione, A Fiandrotti, M Grangetto 2021 IEEE International Conference on Image Processing (ICIP), 3527-3531, 2021 | 2 | 2021 |
| Neural Network-derived perfusion maps: a Model-free approach to computed tomography perfusion in patients with acute ischemic stroke UA Gava, F D'Agata, E Tartaglione, M Grangetto, F Bertolino, ... arXiv preprint arXiv:2101.05992, 2021 | 2 | 2021 |
| Bridging the gap between debiasing and privacy for deep learning CA Barbano, E Tartaglione, M Grangetto Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 2 | 2021 |
| Capsule Networks with Routing Annealing R Renzulli, E Tartaglione, A Fiandrotti, M Grangetto International Conference on Artificial Neural Networks, 529-540, 2021 | 1 | 2021 |
| Dysplasia grading of colorectal polyps through CNN analysis of WSI D Perlo, E Tartaglione, L Bertero, P Cassoni, M Grangetto arXiv preprint arXiv:2102.05498, 2021 | 1 | 2021 |
| Unitopatho L Bertero, CAM Barbano, D Perlo, E Tartaglione, P Cassoni, M Grangetto, ... IEEE Dataport, 2021 | 1 | 2021 |
