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2020 – today
- 2025
[j7]Giommaria Pilo, Nour Hezbri, André Pereira e Ferreira, Victor Quétu, Enzo Tartaglione:
LayerFold: A Python library to reduce the depth of neural networks. SoftwareX 29: 102030 (2025)- [j6]Alberto Presta, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto:
STanH: Parametric Quantization for Variable Rate Learned Image Compression. IEEE Trans. Image Process. 34: 639-651 (2025) - [i56]Haicheng Wang, Zhemeng Yu, Gabriele Spadaro, Chen Ju, Victor Quétu, Enzo Tartaglione:
FOLDER: Accelerating Multi-modal Large Language Models with Enhanced Performance. CoRR abs/2501.02430 (2025) - 2024
- [b1]Enzo Tartaglione:
From Model Complexity Reduction to Feature Selection in Deep Learning: a Regularization Story. (De la réduction de la complexité des modèles à la sélection des caractéristiques dans l'apprentissage profond : une histoire de régularisation). Polytechnic Institute of Paris, Palaiseau, France, 2024 - [c48]Victor Quétu, Enzo Tartaglione:
DSD²: Can We Dodge Sparse Double Descent and Compress the Neural Network Worry-Free? AAAI 2024: 14749-14757 - [c47]Carl De Sousa Trias, Mihai Petru Mitrea, Attilio Fiandrotti, Marco Cagnazzo
, Sumanta Chaudhuri, Enzo Tartaglione:
Find the Lady: Permutation and Re-synchronization of Deep Neural Networks. AAAI 2024: 21001-21009 - [c46]Alberto Presta, Gabriele Spadaro, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto:
Domain Adaptation for Learned Image Compression with Supervised Adapters. DCC 2024: 33-42 - [c45]Francesco Di Sario, Riccardo Renzulli, Enzo Tartaglione, Marco Grangetto:
Boost Your NeRF: A Model-Agnostic Mixture of Experts Framework for High Quality and Efficient Rendering. ECCV (83) 2024: 176-192 - [c44]Imad Eddine Marouf, Subhankar Roy, Enzo Tartaglione, Stéphane Lathuilière:
Weighted Ensemble Models Are Strong Continual Learners. ECCV (71) 2024: 306-324 - [c43]Rémi Nahon, Ivan Luiz De Moura Matos, Van-Tam Nguyen, Enzo Tartaglione:
Debiasing Surgeon: Fantastic Weights and How to Find Them. ECCV (85) 2024: 435-452 - [c42]Carl De Sousa Trias, Mihai Mitrea, Attilio Fiandrotti, Marco Cagnazzo, Sumanta Chaudhuri, Enzo Tartaglione:
WaterMAS: Sharpness-Aware Maximization for Neural Network Watermarking. ICPR (5) 2024: 301-317 - [c41]Le-Trung Nguyen, Aël Quélennec, Enzo Tartaglione, Samuel Tardieu, Van-Tam Nguyen:
Activation Map Compression through Tensor Decomposition for Deep Learning. NeurIPS 2024 - [c40]Victor Quétu, Zhu Liao, Enzo Tartaglione:
The Simpler The Better: An Entropy-Based Importance Metric to Reduce Neural Networks' Depth. ECML/PKDD (6) 2024: 92-108 - [c39]Aël Quélennec, Enzo Tartaglione, Pavlo Mozharovskyi, Van-Tam Nguyen:
Towards On-Device Learning on the Edge: Ways to Select Neurons to Update Under a Budget Constraint. WACV (Workshops) 2024: 685-694 - [c38]Imad Eddine Marouf, Enzo Tartaglione, Stéphane Lathuilière:
Mini but Mighty: Finetuning ViTs with Mini Adapters. WACV 2024: 1721-1730 - [i55]Rémi Nahon, Ivan Luiz De Moura Matos, Van-Tam Nguyen, Enzo Tartaglione:
Debiasing surgeon: fantastic weights and how to find them. CoRR abs/2403.14200 (2024) - [i54]Alberto Presta, Gabriele Spadaro, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto:
Domain Adaptation for Learned Image Compression with Supervised Adapters. CoRR abs/2404.15591 (2024) - [i53]Zhu Liao, Victor Quétu, Van-Tam Nguyen, Enzo Tartaglione:
NEPENTHE: Entropy-Based Pruning as a Neural Network Depth's Reducer. CoRR abs/2404.16890 (2024) - [i52]Victor Quétu, Zhu Liao, Enzo Tartaglione:
The Simpler The Better: An Entropy-Based Importance Metric To Reduce Neural Networks' Depth. CoRR abs/2404.18949 (2024) - [i51]Victor Quétu, Nour Hezbri, Enzo Tartaglione:
LaCoOT: Layer Collapse through Optimal Transport. CoRR abs/2406.08933 (2024) - [i50]Muhammad Salman Ali, Maryam Qamar, Sung-Ho Bae, Enzo Tartaglione:
Trimming the Fat: Efficient Compression of 3D Gaussian Splats through Pruning. CoRR abs/2406.18214 (2024) - [i49]Francesco Di Sario, Riccardo Renzulli, Enzo Tartaglione, Marco Grangetto:
Boost Your NeRF: A Model-Agnostic Mixture of Experts Framework for High Quality and Efficient Rendering. CoRR abs/2407.10389 (2024) - [i48]Massimiliano Ciranni, Luca Molinaro, Carlo Alberto Barbano, Attilio Fiandrotti, Vittorio Murino, Vito Paolo Pastore, Enzo Tartaglione:
Say My Name: a Model's Bias Discovery Framework. CoRR abs/2408.09570 (2024) - [i47]Dorian Gailhard, Enzo Tartaglione, Lirida Naviner de Barros, Jhony H. Giraldo:
HYGENE: A Diffusion-based Hypergraph Generation Method. CoRR abs/2408.16457 (2024) - [i46]Carl De Sousa Trias, Mihai Mitrea, Attilio Fiandrotti, Marco Cagnazzo, Sumanta Chaudhuri, Enzo Tartaglione:
WaterMAS: Sharpness-Aware Maximization for Neural Network Watermarking. CoRR abs/2409.03902 (2024) - [i45]Maxime Girard, Victor Quétu, Samuel Tardieu, Van-Tam Nguyen, Enzo Tartaglione:
Memory-Optimized Once-For-All Network. CoRR abs/2409.05900 (2024) - [i44]Alberto Presta, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto:
STanH : Parametric Quantization for Variable Rate Learned Image Compression. CoRR abs/2410.00557 (2024) - [i43]Gabriele Spadaro, Marco Grangetto, Attilio Fiandrotti, Enzo Tartaglione, Jhony H. Giraldo:
WiGNet: Windowed Vision Graph Neural Network. CoRR abs/2410.00807 (2024) - [i42]Gabriele Spadaro, Alberto Presta, Enzo Tartaglione, Jhony H. Giraldo, Marco Grangetto, Attilio Fiandrotti:
GABIC: Graph-based Attention Block for Image Compression. CoRR abs/2410.02981 (2024) - [i41]Muhammad Salman Ali, Sung-Ho Bae, Enzo Tartaglione:
ELMGS: Enhancing memory and computation scaLability through coMpression for 3D Gaussian Splatting. CoRR abs/2410.23213 (2024) - [i40]Le-Trung Nguyen, Aël Quélennec, Enzo Tartaglione, Samuel Tardieu, Van-Tam Nguyen:
Activation Map Compression through Tensor Decomposition for Deep Learning. CoRR abs/2411.06346 (2024) - [i39]Alberto Presta, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto, Pamela C. Cosman:
Efficient Progressive Image Compression with Variance-aware Masking. CoRR abs/2411.10185 (2024) - [i38]Zhu Liao, Nour Hezbri, Victor Quétu, Van-Tam Nguyen, Enzo Tartaglione:
Till the Layers Collapse: Compressing a Deep Neural Network through the Lenses of Batch Normalization Layers. CoRR abs/2412.15077 (2024) - 2023
- [j5]Umberto A. Gava, Federico D'Agata, Enzo Tartaglione, Riccardo Renzulli, Marco Grangetto, Francesca Bertolino, Ambra Santonocito, Edwin Bennink, Giacomo Vaudano, Andrea Boghi, Mauro Bergui:
Neural network-derived perfusion maps: A model-free approach to computed tomography perfusion in patients with acute ischemic stroke. Frontiers Neuroinformatics 17 (2023) - [j4]Enzo Tartaglione, Francesca Gennari, Victor Quétu, Marco Grangetto:
Disentangling private classes through regularization. Neurocomputing 554: 126612 (2023) - [c37]Carl De Sousa Trias, Mihai Mitrea, Enzo Tartaglione, Attilio Fiandrotti, Marco Cagnazzo, Sumanta Chaudhuri:
A Hitchhiker's Guide to White-Box Neural Network Watermarking Robustness. EUVIP 2023: 1-6 - [c36]Melan Vijayaratnam, Marco Cagnazzo, Giuseppe Valenzise, Enzo Tartaglione:
All Predictions Matter: an Online Video Prediction Approach. EUVIP 2023: 1-5 - [c35]Rémi Nahon, Van-Tam Nguyen, Enzo Tartaglione:
Mining bias-target Alignment from Voronoi Cells. ICCV 2023: 4923-4932 - [c34]Zhu Liao, Victor Quétu, Van-Tam Nguyen, Enzo Tartaglione:
Can Unstructured Pruning Reduce the Depth in Deep Neural Networks? ICCV (Workshops) 2023: 1394-1398 - [c33]Ziyu Li, Enzo Tartaglione, Van-Tam Nguyen:
SCoTTi: Save Computation at Training Time with an adaptive framework. ICCV (Workshops) 2023: 1435-1444 - [c32]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 - [c31]Francesco Di Sario, Riccardo Renzulli, Enzo Tartaglione, Marco Grangetto:
Two is Better than One: Achieving High-Quality 3D Scene Modeling with a NeRF Ensemble. ICIAP (2) 2023: 320-331 - [c30]Alberto Presta, Attilio Fiandrotti, Enzo Tartaglione, Marco Grangetto:
A Differentiable Entropy Model for Learned Image Compression. ICIAP (1) 2023: 328-339 - [c29]Victor Quétu, Marta Milovanovic, Enzo Tartaglione:
Sparse Double Descent in Vision Transformers: Real or Phantom Threat? ICIAP (2) 2023: 490-502 - [c28]Victor Quétu, Enzo Tartaglione:
Dodging the Double Descent in Deep Neural Networks. ICIP 2023: 1625-1629 - [c27]Carlo Alberto Barbano, Benoit Dufumier, Enzo Tartaglione, Marco Grangetto, Pietro Gori:
Unbiased Supervised Contrastive Learning. ICLR 2023 - [c26]Olivier Laurent, Adrien Lafage, Enzo Tartaglione, Geoffrey Daniel, Jean-Marc Martinez, Andrei Bursuc, Gianni Franchi:
Packed Ensembles for efficient uncertainty estimation. ICLR 2023 - [c25]Marta Milovanovic, Enzo Tartaglione, Marco Cagnazzo, Félix Henry:
Learn How to Prune Pixels for Multi-View Neural Image-Based Synthesis. ICME Workshops 2023: 158-163 - [c24]Andrea Bragagnolo, Enzo Tartaglione, Gianluca Dalmasso, Marco Grangetto:
A round-trip journey in pruned artificial neural networks. Ital-IA 2023: 561-566 - [c23]Yinghao Wang, Rémi Nahon, Enzo Tartaglione, Pavlo Mozharovskyi, Van-Tam Nguyen:
Optimized preprocessing and Tiny ML for Attention State Classification. SSP 2023: 695-699 - [c22]Van-Tam Nguyen, Enzo Tartaglione, Tuan Dinh:
AIoT-based Neural Decoding and Neurofeedback for Accelerated Cognitive Training: Vision, Directions and Preliminary Results. SSP 2023: 705-709 - [c21]Melan Vijayaratnam, Marta Milovanovic, Marco Cagnazzo, Enzo Tartaglione, Giuseppe Valenzise:
Unified Measures for the Rate-Distortion-Latency Trade-off. VCIP 2023: 1-5 - [c20]Chenxi Lola Deng, Enzo Tartaglione:
Compressing Explicit Voxel Grid Representations: fast NeRFs become also small. WACV 2023: 1236-1245 - [i37]Victor Quétu, Enzo Tartaglione:
Dodging the Double Descent in Deep Neural Networks. CoRR abs/2302.13259 (2023) - [i36]Victor Quétu, Enzo Tartaglione:
Dodging the Sparse Double Descent. CoRR abs/2303.01213 (2023) - [i35]Yinghao Wang, Rémi Nahon, Enzo Tartaglione, Pavlo Mozharovskyi, Van-Tam Nguyen:
Optimized preprocessing and Tiny ML for Attention State Classification. CoRR abs/2303.11371 (2023) - [i34]Marta Milovanovic, Enzo Tartaglione, Marco Cagnazzo, Félix Henry:
Learn how to Prune Pixels for Multi-view Neural Image-based Synthesis. CoRR abs/2305.03572 (2023) - [i33]Rémi Nahon, Van-Tam Nguyen, Enzo Tartaglione:
Mining bias-target Alignment from Voronoi Cells. CoRR abs/2305.03691 (2023) - [i32]Victor Quétu, Marta Milovanovic, Enzo Tartaglione:
Sparse Double Descent in Vision Transformers: real or phantom threat? CoRR abs/2307.14253 (2023) - [i31]Zhu Liao, Victor Quétu, Van-Tam Nguyen, Enzo Tartaglione:
Can Unstructured Pruning Reduce the Depth in Deep Neural Networks? CoRR abs/2308.06619 (2023) - [i30]Imad Eddine Marouf, Subhankar Roy, Enzo Tartaglione, Stéphane Lathuilière:
Rethinking Class-incremental Learning in the Era of Large Pre-trained Models via Test-Time Adaptation. CoRR abs/2310.11482 (2023) - [i29]Imad Eddine Marouf, Enzo Tartaglione, Stéphane Lathuilière:
Mini but Mighty: Finetuning ViTs with Mini Adapters. CoRR abs/2311.03873 (2023) - [i28]Aël Quélennec, Enzo Tartaglione, Pavlo Mozharovskyi, Van-Tam Nguyen:
Towards On-device Learning on the Edge: Ways to Select Neurons to Update under a Budget Constraint. CoRR abs/2312.05282 (2023) - [i27]Imad Eddine Marouf, Subhankar Roy, Enzo Tartaglione, Stéphane Lathuilière:
Weighted Ensemble Models Are Strong Continual Learners. CoRR abs/2312.08977 (2023) - [i26]Ziyu Lin, Enzo Tartaglione, Van-Tam Nguyen:
SCoTTi: Save Computation at Training Time with an adaptive framework. CoRR abs/2312.12483 (2023) - [i25]Carl De Sousa Trias, Mihai Petru Mitrea, Attilio Fiandrotti, Marco Cagnazzo, Sumanta Chaudhuri, Enzo Tartaglione:
Find the Lady: Permutation and Re-Synchronization of Deep Neural Networks. CoRR abs/2312.14182 (2023) - 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]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) - [c19]Enzo Tartaglione:
Information Removal at the bottleneck in Deep Neural Networks. BMVC 2022: 488 - [c18]Carlo Alberto Barbano, Enzo Tartaglione, Claudio Berzovini, Marco Calandri, Marco Grangetto:
A Two-Step Radiologist-Like Approach for Covid-19 Computer-Aided Diagnosis from Chest X-Ray Images. ICIAP (1) 2022: 173-184 - [c17]Daniele Perlo, Enzo Tartaglione, Umberto A. Gava, Federico D'Agata, Edwin Benninck, Mauro Bergui:
UniToBrain Dataset: A Brain Perfusion Dataset. ICIAP Workshops (1) 2022: 498-509 - [c16]Enzo Tartaglione:
The Rise of the Lottery Heroes: Why Zero-Shot Pruning is Hard. ICIP 2022: 2361-2365 - [c15]Andrea Bragagnolo, Enzo Tartaglione, Marco Grangetto:
To update or not to update? Neurons at equilibrium in deep models. NeurIPS 2022 - [p1]Marco Aldinucci, David Atienza, Federico Bolelli, Mónica Caballero, Iacopo Colonnelli, José Flich, Jon Ander Gómez, David González, Costantino Grana, Marco Grangetto, Simone Leo, Pedro López, Dana Oniga, Roberto Paredes, Luca Pireddu, Eduardo Quiñones, Tatiana Silva, Enzo Tartaglione, Marina Zapater:
The DeepHealth Toolkit: A Key European Free and Open-Source Software for Deep Learning and Computer Vision Ready to Exploit Heterogeneous HPC and Cloud Architectures. Technologies and Applications for Big Data Value 2022: 183-202 - [i24]Enzo Tartaglione:
The rise of the lottery heroes: why zero-shot pruning is hard. CoRR abs/2202.12400 (2022) - [i23]Riccardo Renzulli, Enzo Tartaglione, Marco Grangetto:
REM: Routing Entropy Minimization for Capsule Networks. CoRR abs/2204.01298 (2022) - [i22]Carlo Alberto Barbano, Enzo Tartaglione, Marco Grangetto:
Unsupervised Learning of Unbiased Visual Representations. CoRR abs/2204.12941 (2022) - [i21]Enzo Tartaglione, Francesca Gennari, Marco Grangetto:
Disentangling private classes through regularization. CoRR abs/2207.02000 (2022) - [i20]Andrea Bragagnolo, Enzo Tartaglione, Marco Grangetto:
To update or not to update? Neurons at equilibrium in deep models. CoRR abs/2207.09455 (2022) - [i19]Daniele Perlo, Enzo Tartaglione, Umberto A. Gava, Federico D'Agata, Edwin Benninck, Mauro Bergui:
UniToBrain dataset: a Brain Perfusion Dataset. CoRR abs/2208.00650 (2022) - [i18]Enzo Tartaglione:
Information Removal at the bottleneck in Deep Neural Networks. CoRR abs/2210.00891 (2022) - [i17]Olivier Laurent, Adrien Lafage, Enzo Tartaglione, Geoffrey Daniel, Jean-Marc Martinez, Andrei Bursuc, Gianni Franchi:
Packed-Ensembles for Efficient Uncertainty Estimation. CoRR abs/2210.09184 (2022) - [i16]Chenxi Lola Deng, Enzo Tartaglione:
Compressing Explicit Voxel Grid Representations: fast NeRFs become also small. CoRR abs/2210.12782 (2022) - [i15]Carlo Alberto Barbano, Benoit Dufumier, Enzo Tartaglione, Marco Grangetto, Pietro Gori:
Unbiased Supervised Contrastive Learning. CoRR abs/2211.05568 (2022) - 2021
- [j1]Enzo Tartaglione, Stéphane Lathuilière, Attilio Fiandrotti, Marco Cagnazzo, Marco Grangetto:
HEMP: High-order entropy minimization for neural network compression. Neurocomputing 461: 244-253 (2021) - [c14]Enzo Tartaglione, Carlo Alberto Barbano, Marco Grangetto:
EnD: Entangling and Disentangling Deep Representations for Bias Correction. CVPR 2021: 13508-13517 - [c13]Riccardo Renzulli, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto:
Capsule Networks with Routing Annealing. ICANN (1) 2021: 529-540 - [c12]Carlo Alberto Barbano, Enzo Tartaglione, Marco Grangetto:
Bridging the gap between debiasing and privacy for deep learning. ICCVW 2021: 3799-3808 - [c11]Carlo Alberto Barbano, Daniele Perlo, Enzo Tartaglione, Attilio Fiandrotti, Luca Bertero, Paola Cassoni, Marco Grangetto:
Unitopatho, A Labeled Histopathological Dataset for Colorectal Polyps Classification and Adenoma Dysplasia Grading. ICIP 2021: 76-80 - [c10]Andrea Bragagnolo, Enzo Tartaglione, Attilio Fiandrotti, Marco Grangetto:
On the Role of Structured Pruning for Neural Network Compression. ICIP 2021: 3527-3531 - [c9]Enzo Tartaglione, Béatrice Biancardi, Maurizio Mancini, Giovanna Varni:
A Hitchhiker's Guide towards Transactive Memory System Modeling in Small Group Interactions. ICMI Companion 2021: 254-262 - [c8]Daniele Perlo, Enzo Tartaglione, Paola Cassoni, Luca Bertero, Marco Grangetto:
Dysplasia Grading of Colorectal Polyps Through Convolutional Neural Network Analysis of Whole Slide Images. MICAD 2021: 325-334 - [d7]Luca Bertero, Carlo Alberto Barbano, Daniele Perlo, Enzo Tartaglione, Paola Cassoni, Marco Grangetto, Attilio Fiandrotti, Alessandro Gambella, Luca Cavallo:
UNITOPATHO. IEEE DataPort, 2021
- [d6]Umberto A. Gava, Federico D'Agata, Edwin Bennink, Enzo Tartaglione, Daniele Perlo, Annamaria Vernone, Francesca Bertolino, Eleonora Ficiarà, Alessandro Cicerale, Fabrizio Pizzagalli, Caterina Guiot, Marco Grangetto, Mauro Bergui:
UniTOBrain. IEEE DataPort, 2021 - [d5]Umberto A. Gava, Federico D'Agata, Edwin Bennink, Enzo Tartaglione, Daniele Perlo, Annamaria Vernone, Francesca Bertolino, Eleonora Ficiarà, Alessandro Cicerale, Fabrizio Pizzagalli, Caterina Guiot, Marco Grangetto, Mauro Bergui:
UniToBrain Dataset. Version V1.4. Zenodo, 2021 [all versions] - [d4]Umberto A. Gava, Federico D'Agata, Edwin Bennink, Enzo Tartaglione, Annamaria Vernone, Francesca Bertolino, Eleonora Ficiarà, Alessandro Cicerale, Fabrizio Pizzagalli, Caterina Guiot, Marco Grangetto, Mauro Bergui:
UniToBrain Dataset. Version V1.0. Zenodo, 2021 [all versions] - [d3]Umberto A. Gava, Federico D'Agata, Edwin Bennink, Enzo Tartaglione, Annamaria Vernone, Francesca Bertolino, Eleonora Ficiarà, Alessandro Cicerale, Fabrizio Pizzagalli, Caterina Guiot, Marco Grangetto, Mauro Bergui:
UniToBrain Dataset. Version V1.1. Zenodo, 2021 [all versions] - [d2]Umberto A. Gava, Federico D'Agata, Edwin Bennink, Enzo Tartaglione, Annamaria Vernone, Francesca Bertolino, Eleonora Ficiarà, Alessandro Cicerale, Fabrizio Pizzagalli, Caterina Guiot, Marco Grangetto, Mauro Bergui:
UniToBrain Dataset. Version V1.2. Zenodo, 2021 [all versions] - [d1]Umberto A. Gava, Federico D'Agata, Edwin Bennink, Enzo Tartaglione, Annamaria Vernone, Francesca Bertolino, Eleonora Ficiarà, Alessandro Cicerale, Fabrizio Pizzagalli, Caterina Guiot, Marco Grangetto, Mauro Bergui:
UniToBrain Dataset. Version V1.3. Zenodo, 2021 [all versions] - [i14]Umberto A. Gava, Federico D'Agata, Enzo Tartaglione, Marco Grangetto, Francesca Bertolino, Ambra Santonocito, Edwin Bennink, Mauro Bergui:
Neural Network-derived perfusion maps: a Model-free approach to computed tomography perfusion in patients with acute ischemic stroke. CoRR abs/2101.05992 (2021) - [i13]Carlo Alberto Barbano, Daniele Perlo, Enzo Tartaglione, Attilio Fiandrotti, Luca Bertero, Paola Cassoni, Marco Grangetto:
UniToPatho, a labeled histopathological dataset for colorectal polyps classification and adenoma dysplasia grading. CoRR abs/2101.09991 (2021) - [i12]Carlo Alberto Barbano, Enzo Tartaglione, Claudio Berzovini, Marco Calandri, Marco Grangetto:
A two-step explainable approach for COVID-19 computer-aided diagnosis from chest x-ray images. CoRR abs/2101.10223 (2021) - [i11]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) - [i10]Daniele Perlo, Enzo Tartaglione, Luca Bertero, Paola Cassoni, Marco Grangetto:
Dysplasia grading of colorectal polyps through CNN analysis of WSI. CoRR abs/2102.05498 (2021) - [i9]Enzo Tartaglione, Carlo Alberto Barbano, Marco Grangetto:
EnD: Entangling and Disentangling deep representations for bias correction. CoRR abs/2103.02023 (2021) - [i8]Enzo Tartaglione, Stéphane Lathuilière, Attilio Fiandrotti, Marco Cagnazzo, Marco Grangetto:
HEMP: High-order Entropy Minimization for neural network comPression. CoRR abs/2107.05298 (2021) - 2020
- [c7]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 - [c6]Enzo Tartaglione, Marco Grangetto, Davide Cavagnino, Marco Botta:
Delving in the loss landscape to embed robust watermarks into neural networks. ICPR 2020: 1243-1250 - [c5]Enzo Tartaglione, Marco Grangetto:
A non-discriminatory approach to ethical deep learning. TrustCom 2020: 943-950 - [i7]Enzo Tartaglione, Carlo Alberto Barbano, Claudio Berzovini, Marco Calandri, Marco Grangetto:
Unveiling COVID-19 from Chest X-ray with deep learning: a hurdles race with small data. CoRR abs/2004.05405 (2020) - [i6]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) - [i5]Enzo Tartaglione, Marco Grangetto:
A non-discriminatory approach to ethical deep learning. CoRR abs/2008.01430 (2020) - [i4]Enzo Tartaglione, Andrea Bragagnolo, Attilio Fiandrotti, Marco Grangetto:
LOss-Based SensiTivity rEgulaRization: towards deep sparse neural networks. CoRR abs/2011.09905 (2020)
2010 – 2019
- 2019
- [c4]Enzo Tartaglione, Daniele Perlo, Marco Grangetto:
Post-synaptic Potential Regularization Has Potential. ICANN (2) 2019: 187-200 - [c3]Enzo Tartaglione, Marco Grangetto:
Take a Ramble into Solution Spaces for Classification Problems in Neural Networks. ICIAP (1) 2019: 345-355 - [i3]Enzo Tartaglione, Daniele Perlo, Marco Grangetto:
Post-synaptic potential regularization has potential. CoRR abs/1907.08544 (2019) - 2018
- [c2]Enzo Tartaglione, Skjalg Lepsøy, Attilio Fiandrotti, Gianluca Francini:
Learning sparse neural networks via sensitivity-driven regularization. NeurIPS 2018: 3882-3892 - [i2]Enzo Tartaglione, Skjalg Lepsøy, Attilio Fiandrotti, Gianluca Francini:
Learning Sparse Neural Networks via Sensitivity-Driven Regularization. CoRR abs/1810.11764 (2018) - 2017
- [i1]Carlo Baldassi, Federica Gerace, Hilbert J. Kappen, Carlo Lucibello, Luca Saglietti, Enzo Tartaglione, Riccardo Zecchina:
On the role of synaptic stochasticity in training low-precision neural networks. CoRR abs/1710.09825 (2017) - 2015
- [c1]Enzo Tartaglione, Shantanu Dutt:
Communication Scheduling and Buslet Synthesis for Low-Interconnect HLS Designs. ICCAD 2015: 86-93
Coauthor Index
[j6] [c46] [c45] [i54] [i49] [i44] [i43] [i42] [i39] [j5] [j4] [c32] [c31] [c30] [c27] [c24] [j3] [j2] [c18] [c15] [p1] [i23] [i22] [i21] [i20] [i15] [j1] [c14] [c13] [c12] [c11] [c10] [c8] [d7] [d6] [d5] [d4] [d3] [d2] [d1] [i14] [i13] [i12] [i11] [i10] [i9] [i8] [c7] [c6] [c5] [i7] [i6] [i5] [i4] [c4] [c3] [i3]
Van Tam Nguyen
aka: Van-Tam Nguyen
aka: Van-Tam Nguyen
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