TARTAGLIONE, Enzo
TARTAGLIONE, Enzo
MATEMATICA "GIUSEPPE PEANO"
A non-discriminatory approach to ethical deep learning
2020-01-01 Tartaglione E.; Grangetto M.
A Two-Step Radiologist-Like Approach for Covid-19 Computer-Aided Diagnosis from Chest X-Ray Images
2022-01-01 Barbano Carlo Alberto Maria; Tartaglione E.; Berzovini C.; Calandri M.; Grangetto M.
Applications of AI and HPC in the Health Domain
2022-01-01 Oniga D.; Cantalupo B.; Tartaglione E.; Perlo D.; Grangetto M.; Aldinucci M.; Bolelli F.; Pollastri F.; Cancilla M.; Canalini L.; Grana C.; Alcalde C.M.; Cardillo F.A.; Florea M.
Bridging the gap between debiasing and privacy for deep learning
2021-01-01 Barbano, Carlo Alberto; Tartaglione, Enzo; Grangetto, Marco
Capsule Networks with Routing Annealing
2021-01-01 Renzulli R.; Tartaglione E.; Fiandrotti A.; Grangetto M.
Compressing Explicit Voxel Grid Representations: fast NeRFs become also small
2023-01-01 Deng, Chenxi Lola; Tartaglione, Enzo
Delving in the loss landscape to embed robust watermarks into neural networks
2020-01-01 Tartaglione E.; Grangetto M.; Cavagnino D.; Botta M.
Disentangling private classes through regularization
2023-01-01 Tartaglione E.; Gennari F.; Quetu V.; Grangetto M.
Dysplasia Grading of Colorectal Polyps Through Convolutional Neural Network Analysis of Whole Slide Images
2021-01-01 Perlo D.; Tartaglione E.; Bertero L.; Cassoni P.; Grangetto M.
EnD: Entangling and Disentangling Deep Representations for Bias Correction
2021-01-01 Enzo Tartaglione, Carlo Alberto Barbano, Marco Grangetto
HEMP: High-order entropy minimization for neural network compression
2021-01-01 Tartaglione E.; Lathuiliere S.; Fiandrotti A.; Cagnazzo M.; Grangetto M.
LOss-Based SensiTivity rEgulaRization: towards deep sparse neural networks
2020-01-01 Enzo Tartaglione; Andrea Bragagnolo; Marco Grangetto; Skjalg Lepsoy
LOss-Based SensiTivity rEgulaRization: Towards deep sparse neural networks
2022-01-01 Tartaglione, Enzo; Bragagnolo, Andrea; Fiandrotti, Attilio; Grangetto, Marco
Neural network-derived perfusion maps: A model-free approach to computed tomography perfusion in patients with acute ischemic stroke
2023-01-01 Gava, Umberto A; D'Agata, Federico; Tartaglione, Enzo; Renzulli, Riccardo; Grangetto, Marco; Bertolino, Francesca; Santonocito, Ambra; Bennink, Edwin; Vaudano, Giacomo; Boghi, Andrea; Bergui, Mauro
On the Role of Structured Pruning for Neural Network Compression
2021-01-01 Bragagnolo, Andrea; Tartaglione, Enzo; Fiandrotti, Attilio; Grangetto, Marco
Post-synaptic Potential Regularization Has Potential
2019-01-01 Tartaglione, Enzo; Perlo, Daniele; Grangetto, Marco
Pruning Artificial Neural Networks: A Way to Find Well-Generalizing, High-Entropy Sharp Minima
2020-01-01 Tartaglione E.; Bragagnolo A.; Grangetto M.
SeReNe: Sensitivity-Based Regularization of Neurons for Structured Sparsity in Neural Networks
2021-01-01 Tartaglione, Enzo; Bragagnolo, Andrea; Odierna, Francesco; Fiandrotti, Attilio; Grangetto, Marco
Take a Ramble into Solution Spaces for Classification Problems in Neural Networks
2019-01-01 Tartaglione, Enzo; Grangetto, Marco
The DeepHealth HPC Infrastructure: Leveraging Heterogenous HPC and Cloud Computing Infrastructures for IA-based Medical Solutions
2022-01-01 Eduardo Quiñones, Jesus Perales, Jorge Ejarque, Asaf Badouh, Santiago Marco, Fabrice Auzanneau, François Galea, David González, José Ramón Hervás, Tatiana Silva, Iacopo Colonnelli, Barbara Cantalupo, Marco Aldinucci, Enzo Tartaglione, Rafael Tornero, José Flich, Jose Maria Martínez, David Rodriguez, Izan Catalán, Jorge García, Carles Hernández
Titolo | Data di pubblicazione | Autore(i) | File |
---|---|---|---|
A non-discriminatory approach to ethical deep learning | 2020 | Tartaglione E.; Grangetto M. | |
A Two-Step Radiologist-Like Approach for Covid-19 Computer-Aided Diagnosis from Chest X-Ray Images | 2022 | Barbano Carlo Alberto Maria; Tartaglione E.; Berzovini C.; Calandri M.; Grangetto M. | |
Applications of AI and HPC in the Health Domain | 2022 | Oniga D.; Cantalupo B.; Tartaglione E.; Perlo D.; Grangetto M.; Aldinucci M.; Bolelli F.; Pollastri F.; Cancilla M.; Canalini L.; Grana C.; Alcalde C.M.; Cardillo F.A.; Florea M. | |
Bridging the gap between debiasing and privacy for deep learning | 2021 | Barbano, Carlo Alberto; Tartaglione, Enzo; Grangetto, Marco | |
Capsule Networks with Routing Annealing | 2021 | Renzulli R.; Tartaglione E.; Fiandrotti A.; Grangetto M. | |
Compressing Explicit Voxel Grid Representations: fast NeRFs become also small | 2023 | Deng, Chenxi Lola; Tartaglione, Enzo | |
Delving in the loss landscape to embed robust watermarks into neural networks | 2020 | Tartaglione E.; Grangetto M.; Cavagnino D.; Botta M. | |
Disentangling private classes through regularization | 2023 | Tartaglione E.; Gennari F.; Quetu V.; Grangetto M. | |
Dysplasia Grading of Colorectal Polyps Through Convolutional Neural Network Analysis of Whole Slide Images | 2021 | Perlo D.; Tartaglione E.; Bertero L.; Cassoni P.; Grangetto M. | |
EnD: Entangling and Disentangling Deep Representations for Bias Correction | 2021 | Enzo Tartaglione, Carlo Alberto Barbano, Marco Grangetto | |
HEMP: High-order entropy minimization for neural network compression | 2021 | Tartaglione E.; Lathuiliere S.; Fiandrotti A.; Cagnazzo M.; Grangetto M. | |
LOss-Based SensiTivity rEgulaRization: towards deep sparse neural networks | 2020 | Enzo Tartaglione; Andrea Bragagnolo; Marco Grangetto; Skjalg Lepsoy | |
LOss-Based SensiTivity rEgulaRization: Towards deep sparse neural networks | 2022 | Tartaglione, Enzo; Bragagnolo, Andrea; Fiandrotti, Attilio; Grangetto, Marco | |
Neural network-derived perfusion maps: A model-free approach to computed tomography perfusion in patients with acute ischemic stroke | 2023 | Gava, Umberto A; D'Agata, Federico; Tartaglione, Enzo; Renzulli, Riccardo; Grangetto, Marco; Bertolino, Francesca; Santonocito, Ambra; Bennink, Edwin; Vaudano, Giacomo; Boghi, Andrea; Bergui, Mauro | |
On the Role of Structured Pruning for Neural Network Compression | 2021 | Bragagnolo, Andrea; Tartaglione, Enzo; Fiandrotti, Attilio; Grangetto, Marco | |
Post-synaptic Potential Regularization Has Potential | 2019 | Tartaglione, Enzo; Perlo, Daniele; Grangetto, Marco | |
Pruning Artificial Neural Networks: A Way to Find Well-Generalizing, High-Entropy Sharp Minima | 2020 | Tartaglione E.; Bragagnolo A.; Grangetto M. | |
SeReNe: Sensitivity-Based Regularization of Neurons for Structured Sparsity in Neural Networks | 2021 | Tartaglione, Enzo; Bragagnolo, Andrea; Odierna, Francesco; Fiandrotti, Attilio; Grangetto, Marco | |
Take a Ramble into Solution Spaces for Classification Problems in Neural Networks | 2019 | Tartaglione, Enzo; Grangetto, Marco | |
The DeepHealth HPC Infrastructure: Leveraging Heterogenous HPC and Cloud Computing Infrastructures for IA-based Medical Solutions | 2022 | Eduardo Quiñones, Jesus Perales, Jorge Ejarque, Asaf Badouh, Santiago Marco, Fabrice Auzanneau, François Galea, David González, José Ramón Hervás, Tatiana Silva, Iacopo Colonnelli, Barbara Cantalupo, Marco Aldinucci, Enzo Tartaglione, Rafael Tornero, José Flich, Jose Maria Martínez, David Rodriguez, Izan Catalán, Jorge García, Carles Hernández |