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Gabriele Ciravegna
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- affiliation: Politecnico di Torino, Turin, Italy
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2020 – today
- 2024
- [j8]Giansalvo Cirrincione, Vincenzo Randazzo, Pietro Barbiero, Gabriele Ciravegna, Eros Pasero:
Gradient-Based Competitive Learning: Theory. Cogn. Comput. 16(2): 608-623 (2024) - [j7]Alessandro Betti, Gabriele Ciravegna, Marco Gori, Stefano Melacci, Kevin Mottin, Frédéric Precioso:
A new perspective on optimizers: leveraging moreau-yosida approximation in gradient-based learning. Intelligenza Artificiale 18(2): 301-311 (2024) - [j6]Matteo Tiezzi, Gabriele Ciravegna, Marco Gori:
Graph Neural Networks for Graph Drawing. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4668-4681 (2024) - [c18]Gabriele Ciravegna, Alkis Koudounas, Marco Fantini, Tania Cerquitelli, Elena Baralis, Erika Crosetti, Giovanni Succo:
Non-invasive AI-powered Diagnostics: The case of Voice-Disorder Detection. EDBT/ICDT Workshops 2024 - [c17]Gabriele Ciravegna, Mateo Espinosa Zarlenga, Pietro Barbiero, Francesco Giannini, Zohreh Shams, Damien Garreau, Mateja Jamnik, Tania Cerquitelli:
Workshop on Human-Interpretable AI. KDD 2024: 6708-6709 - [i17]Francesco De Santis, Philippe Bich, Gabriele Ciravegna, Pietro Barbiero, Danilo Giordano, Tania Cerquitelli:
Self-supervised Interpretable Concept-based Models for Text Classification. CoRR abs/2406.14335 (2024) - [i16]Alkis Koudounas, Gabriele Ciravegna, Marco Fantini, Giovanni Succo, Erika Crosetti, Tania Cerquitelli, Elena Baralis:
Voice Disorder Analysis: a Transformer-based Approach. CoRR abs/2406.14693 (2024) - [i15]David Debot, Pietro Barbiero, Francesco Giannini, Gabriele Ciravegna, Michelangelo Diligenti, Giuseppe Marra:
Interpretable Concept-Based Memory Reasoning. CoRR abs/2407.15527 (2024) - 2023
- [j5]Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Marco Gori, Pietro Liò, Marco Maggini, Stefano Melacci:
Logic Explained Networks. Artif. Intell. 314: 103822 (2023) - [c16]Alessandro Betti, Gabriele Ciravegna, Marco Gori, Stefano Melacci, Kevin Mottin, Frédéric Precioso:
Toward Novel Optimizers: A Moreau-Yosida View of Gradient-Based Learning. AI*IA 2023: 218-230 - [c15]Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Lio, Frédéric Precioso, Mateja Jamnik, Giuseppe Marra:
Interpretable Neural-Symbolic Concept Reasoning. ICML 2023: 1801-1825 - [c14]Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Liò, Frédéric Precioso, Mateja Jamnik, Giuseppe Marra:
Interpretable Neural-Symbolic Concept Reasoning. NeSy 2023: 422-423 - [c13]Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Marco Gori, Pietro Liò, Marco Maggini, Stefano Melacci:
Logic Explained Networks. NeSy 2023: 432-433 - [c12]Gabriele Ciravegna, Frédéric Precioso, Alessandro Betti, Kevin Mottin, Marco Gori:
Knowledge-Driven Active Learning. ECML/PKDD (1) 2023: 38-54 - [c11]Lucie Charlotte Magister, Pietro Barbiero, Dmitry Kazhdan, Federico Siciliano, Gabriele Ciravegna, Fabrizio Silvestri, Mateja Jamnik, Pietro Liò:
Concept Distillation in Graph Neural Networks. xAI (3) 2023: 233-255 - [p6]Gabriele Ciravegna, Francesco Giannini, Pietro Barbiero, Marco Gori, Pietro Lio, Marco Maggini, Stefano Melacci:
Learning Logic Explanations by Neural Networks. Compendium of Neurosymbolic Artificial Intelligence 2023: 547-558 - [i14]Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Lio', Frédéric Precioso, Mateja Jamnik, Giuseppe Marra:
Interpretable Neural-Symbolic Concept Reasoning. CoRR abs/2304.14068 (2023) - [i13]Pietro Barbiero, Francesco Giannini, Gabriele Ciravegna, Michelangelo Diligenti, Giuseppe Marra:
Relational Concept Based Models. CoRR abs/2308.11991 (2023) - [i12]Eleonora Poeta, Gabriele Ciravegna, Eliana Pastor, Tania Cerquitelli, Elena Baralis:
Concept-based Explainable Artificial Intelligence: A Survey. CoRR abs/2312.12936 (2023) - 2022
- [b1]Gabriele Ciravegna:
On the Two-fold Role of Logic Constraints in Deep Learning. Polytechnic University of Turin, Italy, 2022 - [j4]Daniele Canavese, Leonardo Regano, Cataldo Basile, Gabriele Ciravegna, Antonio Lioy:
Encryption-agnostic classifiers of traffic originators and their application to anomaly detection. Comput. Electr. Eng. 97: 107621 (2022) - [j3]Marta Lovino, Vincenzo Randazzo, Gabriele Ciravegna, Pietro Barbiero, Elisa Ficarra, Giansalvo Cirrincione:
A survey on data integration for multi-omics sample clustering. Neurocomputing 488: 494-508 (2022) - [j2]Stefano Melacci, Gabriele Ciravegna, Angelo Sotgiu, Ambra Demontis, Battista Biggio, Marco Gori, Fabio Roli:
Domain Knowledge Alleviates Adversarial Attacks in Multi-Label Classifiers. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9944-9959 (2022) - [c10]Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Pietro Lió, Marco Gori, Stefano Melacci:
Entropy-Based Logic Explanations of Neural Networks. AAAI 2022: 6046-6054 - [c9]Rida Ghafoor Hussain, Matteo Tiezzi, Gabriele Ciravegna, Marco Gori:
Minimizing Cross Intersections in Graph Drawing via Linear Splines. ANNPR 2022: 28-39 - [c8]Rishabh Jain, Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Davide Buffelli, Pietro Liò:
Extending Logic Explained Networks to Text Classification. EMNLP 2022: 8838-8857 - [c7]Mateo Espinosa Zarlenga, Pietro Barbiero, Gabriele Ciravegna, Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Zohreh Shams, Frédéric Precioso, Stefano Melacci, Adrian Weller, Pietro Lió, Mateja Jamnik:
Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off. NeurIPS 2022 - [i11]Lucie Charlotte Magister, Pietro Barbiero, Dmitry Kazhdan, Federico Siciliano, Gabriele Ciravegna, Fabrizio Silvestri, Pietro Liò, Mateja Jamnik:
Encoding Concepts in Graph Neural Networks. CoRR abs/2207.13586 (2022) - [i10]Mateo Espinosa Zarlenga, Pietro Barbiero, Gabriele Ciravegna, Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Zohreh Shams, Frédéric Precioso, Stefano Melacci, Adrian Weller, Pietro Liò, Mateja Jamnik:
Concept Embedding Models. CoRR abs/2209.09056 (2022) - [i9]Rishabh Jain, Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Davide Buffelli, Pietro Liò:
Extending Logic Explained Networks to Text Classification. CoRR abs/2211.09732 (2022) - 2021
- [c6]Pietro Barbiero, Gabriele Ciravegna, Vincenzo Randazzo, Eros Pasero, Giansalvo Cirrincione:
Topological Gradient-based Competitive Learning. IJCNN 2021: 1-8 - [i8]Pietro Barbiero, Gabriele Ciravegna, Dobrik Georgiev, Francesco Giannini:
LENs: a Python library for Logic Explained Networks. CoRR abs/2105.11697 (2021) - [i7]Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Pietro Lió, Marco Gori, Stefano Melacci:
Entropy-based Logic Explanations of Neural Networks. CoRR abs/2106.06804 (2021) - [i6]Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini, Marco Gori, Pietro Lió, Marco Maggini, Stefano Melacci:
Logic Explained Networks. CoRR abs/2108.05149 (2021) - [i5]Matteo Tiezzi, Gabriele Ciravegna, Marco Gori:
Graph Neural Networks for Graph Drawing. CoRR abs/2109.10061 (2021) - [i4]Gabriele Ciravegna, Frédéric Precioso, Marco Gori:
Knowledge-driven Active Learning. CoRR abs/2110.08265 (2021) - 2020
- [j1]Giansalvo Cirrincione, Gabriele Ciravegna, Pietro Barbiero, Vincenzo Randazzo, Eros Pasero:
The GH-EXIN neural network for hierarchical clustering. Neural Networks 121: 57-73 (2020) - [c5]Gabriele Ciravegna, Francesco Giannini, Stefano Melacci, Marco Maggini, Marco Gori:
A Constraint-Based Approach to Learning and Explanation. AAAI 2020: 3658-3665 - [c4]Pietro Barbiero, Marta Lovino, Mattia Siviero, Gabriele Ciravegna, Vincenzo Randazzo, Elisa Ficarra, Giansalvo Cirrincione:
Unsupervised Multi-omic Data Fusion: The Neural Graph Learning Network. ICIC (1) 2020: 172-182 - [c3]Gabriele Ciravegna, Francesco Giannini, Marco Gori, Marco Maggini, Stefano Melacci:
Human-Driven FOL Explanations of Deep Learning. IJCAI 2020: 2234-2240 - [p5]Gabriele Ciravegna, Giansalvo Cirrincione, Federica Marcolin, Pietro Barbiero, Nicole Dagnes, Elio Piccolo:
Assessing Discriminating Capability of Geometrical Descriptors for 3D Face Recognition by Using the GH-EXIN Neural Network. Neural Approaches to Dynamics of Signal Exchanges 2020: 223-233 - [p4]Pietro Barbiero, Andrea Bertotti, Gabriele Ciravegna, Giansalvo Cirrincione, Elio Piccolo, Alberto Tonda:
Understanding Cancer Phenomenon at Gene Expression Level by using a Shallow Neural Network Chain. Neural Approaches to Dynamics of Signal Exchanges 2020: 281-290 - [p3]Pietro Barbiero, Andrea Bertotti, Gabriele Ciravegna, Giansalvo Cirrincione, Elio Piccolo:
DNA Microarray Classification: Evolutionary Optimization of Neural Network Hyper-parameters. Neural Approaches to Dynamics of Signal Exchanges 2020: 305-311 - [i3]Stefano Melacci, Gabriele Ciravegna, Angelo Sotgiu, Ambra Demontis, Battista Biggio, Marco Gori, Fabio Roli:
Can Domain Knowledge Alleviate Adversarial Attacks in Multi-Label Classifiers? CoRR abs/2006.03833 (2020) - [i2]Pietro Barbiero, Gabriele Ciravegna, Vincenzo Randazzo, Giansalvo Cirrincione:
Topological Gradient-based Competitive Learning. CoRR abs/2008.09477 (2020) - [i1]Giansalvo Cirrincione, Pietro Barbiero, Gabriele Ciravegna, Vincenzo Randazzo:
Gradient-based Competitive Learning: Theory. CoRR abs/2009.02799 (2020)
2010 – 2019
- 2019
- [p2]Pietro Barbiero, Andrea Bertotti, Gabriele Ciravegna, Giansalvo Cirrincione, Eros Pasero, Elio Piccolo:
Unsupervised Gene Identification in Colorectal Cancer. Quantifying and Processing Biomedical and Behavioral Signals 2019: 219-227 - [p1]Pietro Barbiero, Andrea Bertotti, Gabriele Ciravegna, Giansalvo Cirrincione, Eros Pasero, Elio Piccolo:
Supervised Gene Identification in Colorectal Cancer. Quantifying and Processing Biomedical and Behavioral Signals 2019: 243-251 - 2018
- [c2]Vincenzo Randazzo, Giansalvo Cirrincione, Gabriele Ciravegna, Eros Pasero:
Nonstationary topological learning with bridges and convex polytopes: the G-EXIN neural network. IJCNN 2018: 1-6 - 2017
- [c1]Gabriele Ciravegna, Pietro Barbiero, Giansalvo Cirrincione, Giovanni Squillero, Alberto Tonda:
Discovering Hierarchical Neural Archetype Sets. IIH-MSP (1) 2017: 255-267
Coauthor Index
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last updated on 2024-11-11 21:31 CET by the dblp team
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