Andrea Bragagnolo

According to our database, Andrea Bragagnolo authored at least 15 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

TEP-ones: A simple yet effective approach for transferability estimation of pruned backbones.

Gabriele Spadaro, Andrea Bragagnolo, Riccardo Renzulli, Marco Grangetto, Jhony H. Giraldo, Attilio Fiandrotti, Enzo Tartaglione

Neurocomputing, 2026

Towards a validation-less approach for small data: training with neural velocity.

Gianluca Dalmasso, Andrea Bragagnolo, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto

Neurocomputing, 2026

Cardiac Output Prediction From Echocardiograms: Self-Supervised Learning with Limited Data.

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

Proceedings of the 23rd IEEE International Symposium on Biomedical Imaging, 2026

2025

Neural Velocity for hyperparameter tuning.

Gianluca Dalmasso, Andrea Bragagnolo, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto

Proceedings of the International Joint Conference on Neural Networks, 2025

When Does Pruning Benefit Vision Representations?

Enrico Cassano, Riccardo Renzulli, Andrea Bragagnolo, Marco Grangetto

Proceedings of the Image Analysis and Processing - ICIAP 2025, 2025

2023

A round-trip journey in pruned artificial neural networks.

Andrea Bragagnolo, Enzo Tartaglione, Gianluca Dalmasso, Marco Grangetto

Proceedings of the Italia Intelligenza Artificiale, 2023

Shannon Strikes Again! Entropy-based Pruning in Deep Neural Networks for Transfer Learning under Extreme Memory and Computation Budgets.

Gabriele Spadaro, Riccardo Renzulli, Andrea Bragagnolo, Jhony H. Giraldo, Attilio Fiandrotti, Marco Grangetto, Enzo Tartaglione

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

SeReNe: Sensitivity-Based Regularization of Neurons for Structured Sparsity in Neural Networks.

Enzo Tartaglione, Andrea Bragagnolo, Francesco Odierna, Attilio Fiandrotti, Marco Grangetto

IEEE Trans. Neural Networks Learn. Syst., 2022

Simplify: A Python library for optimizing pruned neural networks.

Andrea Bragagnolo, Carlo Alberto Barbano

SoftwareX, 2022

LOss-Based SensiTivity rEgulaRization: Towards deep sparse neural networks.

Enzo Tartaglione, Andrea Bragagnolo, Attilio Fiandrotti, Marco Grangetto

Neural Networks, 2022

To update or not to update? Neurons at equilibrium in deep models.

Andrea Bragagnolo, Enzo Tartaglione, Marco Grangetto

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Efficient Inference Of Image-Based Neural Network Models In Reconfigurable Systems With Pruning And Quantization.

José Flich, Laura Medina, Izan Catalán, Carles Hernández, Andrea Bragagnolo, Fabrice Auzanneau, David Briand

Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

2021

On the Role of Structured Pruning for Neural Network Compression.

Andrea Bragagnolo, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021

2020

Pruning Artificial Neural Networks: A Way to Find Well-Generalizing, High-Entropy Sharp Minima.

Enzo Tartaglione, Andrea Bragagnolo, Marco Grangetto

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

2018

Cyber-coordinated Simulation Models for Multi-stage Additive Manufacturing of Energy Products.

Hongyue Sun, Giulia Pedrielli, Guanglei Zhao, Andrea Bragagnolo, Chi Zhou, Rong Pan, Wenyao Xu

Proceedings of the 14th IEEE International Conference on Automation Science and Engineering, 2018