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Enzo Tartaglione
Enzo Tartaglione
Associate Professor, Télécom Paris, Institut Polytechnique de Paris
Verified email at telecom-paris.fr - Homepage
Title
Cited by
Cited by
Year
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
2262020
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
1072021
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
942018
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
362021
Compressing explicit voxel grid representations: fast nerfs become also small
CL Deng, E Tartaglione
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023
342023
Loss-based sensitivity regularization: towards deep sparse neural networks
E Tartaglione, A Bragagnolo, A Fiandrotti, M Grangetto
Neural Networks 146, 230-237, 2022
292022
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
272021
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
262018
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
232021
Unbiased Supervised Contrastive Learning
CA Barbano, B Dufumier, E Tartaglione, M Grangetto, P Gori
The Eleventh International Conference on Learning Representations (ICLR), 2022
222022
Packed-Ensembles for Efficient Uncertainty Estimation
O Laurent, A Lafage, E Tartaglione, G Daniel, JM Martinez, A Bursuc, ...
The Eleventh International Conference on Learning Representations (ICLR), 2022
152022
Pruning artificial neural networks: A way to find well-generalizing, high-entropy sharp minima
E Tartaglione, A Bragagnolo, M Grangetto
Artificial Neural Networks and Machine Learning–ICANN 2020: 29th …, 2020
152020
A Two-Step Radiologist-Like Approach for Covid-19 Computer-Aided Diagnosis from Chest X-Ray Images
CA Barbano, E Tartaglione, C Berzovini, M Calandri, M Grangetto
International Conference on Image Analysis and Processing, 173-184, 2022
122022
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
122021
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
112021
To update or not to update? Neurons at equilibrium in deep models
A Bragagnolo, E Tartaglione, M Grangetto
Advances in Neural Information Processing Systems 35, 2022
92022
HEMP: high-order entropy minimization for neural network compression
E Tartaglione, S Lathuilière, A Fiandrotti, M Cagnazzo, M Grangetto
Neurocomputing 461, 244-253, 2021
82021
DSD²: Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free?
V Quétu, E Tartaglione
Proceedings of the AAAI Conference on Artificial Intelligence 38 (13), 14749 …, 2024
7*2024
Can Unstructured Pruning Reduce the Depth in Deep Neural Networks?
Z Liao, V Quétu, VT Nguyen, E Tartaglione
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023
72023
Dysplasia grading of colorectal polyps through convolutional neural network analysis of whole slide images
D Perlo, E Tartaglione, L Bertero, P Cassoni, M Grangetto
International Conference on Medical Imaging and Computer-Aided Diagnosis …, 2021
72021
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