Andrea Bragagnolo

20 papers A* 1B 3Journal 11Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
Cardiac Output Prediction from Echocardiograms: Self-Supervised Learning with Limited Data.
CoRR
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
2026 J jnl
TEP-ones: A simple yet effective approach for transferability estimation of pruned backbones.
Neurocomputing
Gabriele Spadaro, Andrea Bragagnolo, Riccardo Renzulli, Marco Grangetto, Jhony H. Giraldo, Attilio Fiandrotti, Enzo Tartaglione
2025 B conf
Neural Velocity for hyperparameter tuning.
IJCNN
Gianluca Dalmasso, Andrea Bragagnolo, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto
2025 J jnl
Neural Velocity for hyperparameter tuning.
CoRR
Gianluca Dalmasso, Andrea Bragagnolo, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto
2025 — conf
When Does Pruning Benefit Vision Representations?
ICIAP (2)
Enrico Cassano, Riccardo Renzulli, Andrea Bragagnolo, Marco Grangetto
2025 J jnl
When Does Pruning Benefit Vision Representations?
CoRR
Enrico Cassano, Riccardo Renzulli, Andrea Bragagnolo, Marco Grangetto
2023 — conf
A round-trip journey in pruned artificial neural networks.
Ital-IA
Andrea Bragagnolo, Enzo Tartaglione, Gianluca Dalmasso, Marco Grangetto
2023 — conf
Shannon Strikes Again! Entropy-based Pruning in Deep Neural Networks for Transfer Learning under Extreme Memory and Computation Budgets.
ICCV (Workshops)
Gabriele Spadaro, Riccardo Renzulli, Andrea Bragagnolo, Jhony H. Giraldo, Attilio Fiandrotti, Marco Grangetto, Enzo Tartaglione
2022 B conf
Efficient Inference Of Image-Based Neural Network Models In Reconfigurable Systems With Pruning And Quantization.
ICIP
José Flich, Laura Medina, Izan Catalán, Carles Hernández, Andrea Bragagnolo, Fabrice Auzanneau, David Briand
2022 J jnl
LOss-Based SensiTivity rEgulaRization: Towards deep sparse neural networks.
Neural Networks
Enzo Tartaglione, Andrea Bragagnolo, Attilio Fiandrotti, Marco Grangetto
2022 J jnl
SeReNe: Sensitivity-Based Regularization of Neurons for Structured Sparsity in Neural Networks.
IEEE Trans. Neural Networks Learn. Syst.
Enzo Tartaglione, Andrea Bragagnolo, Francesco Odierna, Attilio Fiandrotti, Marco Grangetto
2022 J jnl
Simplify: A Python library for optimizing pruned neural networks.
SoftwareX
Andrea Bragagnolo, Carlo Alberto Barbano
2022 A* conf
To update or not to update? Neurons at equilibrium in deep models.
NeurIPS
Andrea Bragagnolo, Enzo Tartaglione, Marco Grangetto
2022 J jnl
To update or not to update? Neurons at equilibrium in deep models.
CoRR
Andrea Bragagnolo, Enzo Tartaglione, Marco Grangetto
2021 B conf
On the Role of Structured Pruning for Neural Network Compression.
ICIP
Andrea Bragagnolo, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto
2021 J jnl
SeReNe: Sensitivity based Regularization of Neurons for Structured Sparsity in Neural Networks.
CoRR
Enzo Tartaglione, Andrea Bragagnolo, Francesco Odierna, Attilio Fiandrotti, Marco Grangetto
2020 J jnl
LOss-Based SensiTivity rEgulaRization: towards deep sparse neural networks.
CoRR
Enzo Tartaglione, Andrea Bragagnolo, Attilio Fiandrotti, Marco Grangetto
2020 — conf
Pruning Artificial Neural Networks: A Way to Find Well-Generalizing, High-Entropy Sharp Minima.
ICANN (2)
Enzo Tartaglione, Andrea Bragagnolo, Marco Grangetto
2020 J jnl
Pruning artificial neural networks: a way to find well-generalizing, high-entropy sharp minima.
CoRR
Enzo Tartaglione, Andrea Bragagnolo, Marco Grangetto
2018 — conf
Cyber-coordinated Simulation Models for Multi-stage Additive Manufacturing of Energy Products.
CASE
Hongyue Sun, Giulia Pedrielli, Guanglei Zhao, Andrea Bragagnolo, Chi Zhou, Rong Pan, Wenyao Xu