Enzo Tartaglione
Enzo Tartaglione
Télécom Paris
Zweryfikowany adres z telecom-paris.fr - Strona główna
Cytowane przez
Cytowane przez
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
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
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
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
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
Loss-based sensitivity regularization: towards deep sparse neural networks
E Tartaglione, A Bragagnolo, A Fiandrotti, M Grangetto
Neural Networks 146, 230-237, 2022
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
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
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
HEMP: High-order entropy minimization for neural network compression
E Tartaglione, S Lathuilière, A Fiandrotti, M Cagnazzo, M Grangetto
Neurocomputing 461, 244-253, 2021
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
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
Post-synaptic potential regularization has potential
E Tartaglione, D Perlo, M Grangetto
International Conference on Artificial Neural Networks, 187-200, 2019
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
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
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
A non-discriminatory approach to ethical deep learning
E Tartaglione, M Grangetto
2020 IEEE 19th International Conference on Trust, Security and Privacy in …, 2020
Capsule Networks with Routing Annealing
R Renzulli, E Tartaglione, A Fiandrotti, M Grangetto
International Conference on Artificial Neural Networks, 529-540, 2021
Unbiased Supervised Contrastive Learning
CA Barbano, B Dufumier, E Tartaglione, M Grangetto, P Gori
arXiv preprint arXiv:2211.05568, 2022
REM: Routing Entropy Minimization for Capsule Networks
R Renzulli, E Tartaglione, M Grangetto
arXiv preprint arXiv:2204.01298, 2022
Nie można teraz wykonać tej operacji. Spróbuj ponownie później.
Prace 1–20