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ORCIDAndrea Bragagnolo
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2020 – today
- 2026
[j5]Gabriele Spadaro
, Andrea Bragagnolo, Riccardo Renzulli, Marco Grangetto, Jhony H. Giraldo, Attilio Fiandrotti, Enzo Tartaglione:
TEP-ones: A simple yet effective approach for transferability estimation of pruned backbones. Neurocomputing 668: 132209 (2026)- [j4]Gianluca Dalmasso, Andrea Bragagnolo, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto:
Towards a validation-less approach for small data: training with neural velocity. Neurocomputing 696: 134097 (2026) - [c10]Adson Duarte, Davide Vitturini, Emanuele Milillo, Andrea Bragagnolo, Carlo Alberto Barbano, Riccardo Renzulli, Michele Cannito, Federico Giacobbe, Francesco Bruno, Ovidio De Filippo, Fabrizio D'Ascenzo, Marco Grangetto:
Cardiac Output Prediction From Echocardiograms: Self-Supervised Learning with Limited Data. ISBI 2026: 1-4 - [i7]Adson Duarte, Davide Vitturini, Emanuele Milillo, Andrea Bragagnolo, Carlo Alberto Barbano, Riccardo Renzulli, Michele Cannito, Federico Giacobbe, Francesco Bruno, Ovidio De Filippo, Fabrizio D'Ascenzo, Marco Grangetto:
Cardiac Output Prediction from Echocardiograms: Self-Supervised Learning with Limited Data. CoRR abs/2602.13846 (2026) - 2025
- [c9]Enrico Cassano, Riccardo Renzulli, Andrea Bragagnolo, Marco Grangetto:
When Does Pruning Benefit Vision Representations? ICIAP (2) 2025: 152-163 - [c8]Gianluca Dalmasso, Andrea Bragagnolo, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto:
Neural Velocity for hyperparameter tuning. IJCNN 2025: 1-8 - [i6]Enrico Cassano, Riccardo Renzulli, Andrea Bragagnolo, Marco Grangetto:
When Does Pruning Benefit Vision Representations? CoRR abs/2507.01722 (2025) - [i5]Gianluca Dalmasso, Andrea Bragagnolo, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto:
Neural Velocity for hyperparameter tuning. CoRR abs/2507.05309 (2025) - 2023
- [c7]Gabriele Spadaro, Riccardo Renzulli, Andrea Bragagnolo, Jhony H. Giraldo, Attilio Fiandrotti, Marco Grangetto, Enzo Tartaglione:
Shannon Strikes Again! Entropy-based Pruning in Deep Neural Networks for Transfer Learning under Extreme Memory and Computation Budgets. ICCV (Workshops) 2023: 1510-1514 - [c6]Andrea Bragagnolo, Enzo Tartaglione, Gianluca Dalmasso, Marco Grangetto:
A round-trip journey in pruned artificial neural networks. Ital-IA 2023: 561-566 - 2022
- [j3]Enzo Tartaglione, Andrea Bragagnolo, Attilio Fiandrotti, Marco Grangetto:
LOss-Based SensiTivity rEgulaRization: Towards deep sparse neural networks. Neural Networks 146: 230-237 (2022) - [j2]Andrea Bragagnolo, Carlo Alberto Barbano:
Simplify: A Python library for optimizing pruned neural networks. SoftwareX 17: 100907 (2022) - [j1]Enzo Tartaglione, Andrea Bragagnolo, Francesco Odierna, Attilio Fiandrotti, Marco Grangetto:
SeReNe: Sensitivity-Based Regularization of Neurons for Structured Sparsity in Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 33(12): 7237-7250 (2022) - [c5]José Flich, Laura Medina, Izan Catalán, Carles Hernández, Andrea Bragagnolo, Fabrice Auzanneau, David Briand:
Efficient Inference Of Image-Based Neural Network Models In Reconfigurable Systems With Pruning And Quantization. ICIP 2022: 2491-2495 - [c4]Andrea Bragagnolo, Enzo Tartaglione, Marco Grangetto:
To update or not to update? Neurons at equilibrium in deep models. NeurIPS 2022 - [i4]Andrea Bragagnolo, Enzo Tartaglione, Marco Grangetto:
To update or not to update? Neurons at equilibrium in deep models. CoRR abs/2207.09455 (2022) - 2021
- [c3]Andrea Bragagnolo, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto:
On the Role of Structured Pruning for Neural Network Compression. ICIP 2021: 3527-3531 - [i3]Enzo Tartaglione, Andrea Bragagnolo, Francesco Odierna, Attilio Fiandrotti, Marco Grangetto:
SeReNe: Sensitivity based Regularization of Neurons for Structured Sparsity in Neural Networks. CoRR abs/2102.03773 (2021) - 2020
- [c2]Enzo Tartaglione, Andrea Bragagnolo, Marco Grangetto:
Pruning Artificial Neural Networks: A Way to Find Well-Generalizing, High-Entropy Sharp Minima. ICANN (2) 2020: 67-78 - [i2]Enzo Tartaglione, Andrea Bragagnolo, Marco Grangetto:
Pruning artificial neural networks: a way to find well-generalizing, high-entropy sharp minima. CoRR abs/2004.14765 (2020) - [i1]Enzo Tartaglione, Andrea Bragagnolo, Attilio Fiandrotti, Marco Grangetto:
LOss-Based SensiTivity rEgulaRization: towards deep sparse neural networks. CoRR abs/2011.09905 (2020)
2010 – 2019
- 2018
- [c1]Hongyue Sun, Giulia Pedrielli, Guanglei Zhao, Andrea Bragagnolo, Chi Zhou, Rong Pan, Wenyao Xu:
Cyber-coordinated Simulation Models for Multi-stage Additive Manufacturing of Energy Products. CASE 2018: 893-898
Coauthor Index
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last updated on 2026-06-27 06:18 CEST by the dblp team
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