2023
VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming Inproceedings Forthcoming
In: NeurIPS, Forthcoming.
Concept Embedding Models Inproceedings Forthcoming
In: NeurIPS, Forthcoming.
2022
Deepstochlog: Neural stochastic logic programming Inproceedings
In: AAAI, 2022.
A Constraint-Based Approach to Learning and Reasoning Journal Article
In: Neuro-Symbolic Artificial Intelligence: The State of the Art, vol. 342, pp. 192, 2022.
Neuro-Symbolic AI= Neural+ Logical+ Probabilistic AI Journal Article
In: Neuro-Symbolic Artificial Intelligence: The State of the Art, vol. 342, pp. 173, 2022.
2021
Neural markov logic networks Inproceedings
In: UAI, 2021.
Learning Representations for Sub-Symbolic Reasoning Journal Article
In: arXiv preprint arXiv:2106.00393, 2021.
From Statistical Relational to Neural Symbolic Artificial Intelligence: a Survey Journal Article
In: arXiv preprint arXiv:2108.11451, 2021.
Approximate Inference for Neural Probabilistic Logic Programming. Inproceedings
In: KR, pp. 475–486, 2021.
DEEP GENERATIVE MODELS WITH PROBABILISTIC LOGIC PRIORS Journal Article
In: 2021.
Deep constraint-based propagation in graph neural networks Journal Article
In: IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 2, pp. 727–739, 2021.
2020
Local propagation in constraint-based neural network Journal Article
In: IJCNN 2020, 2020.
A lagrangian approach to information propagation in graph neural networks Inproceedings
In: ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August, 2020.
From Statistical Relational to Neuro-Symbolic Artificial Intelligence Inproceedings
In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, pp. 4943–4950, Christian Bessiere 2020.
Lagrangian Propagation Graph Neural Networks Inproceedings
In: ECAI, 2020.
Bridging symbolic and subsymbolic reasoning with MiniMax Entropy models. PhD Thesis
University of Florence, 2020.
Inference in Relational Neural Machines Inproceedings
In: Proceedings of the First International Workshop on New Foundations for Human-Centered AI (NeHuAI) co-located with 24th European Conference on Artificial Intelligence (ECAI 2020), Santiago de Compostella, Spain, September 4, 2020., pp. 71–74, 2020.
Online Learning of Non-Markovian Reward Models Journal Article
In: ICART, 2020.
Relational Neural Machines Inproceedings
In: ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August, pp. 1340–1347, 2020.
2019
Constraint-based visual generation Inproceedings
In: International Conference on Artificial Neural Networks, pp. 565–577, Springer, Cham 2019.
Integrating learning and reasoning with deep logic models Inproceedings
In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML 2019, 2019.
On the relation between Loss Functions and T-Norms Inproceedings
In: International Conference on Inductive Logic Programming, 2019.
Learning in text streams: Discovery and disambiguation of entity and relation instances Journal Article
In: IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 11, pp. 4475–4486, 2019.
LYRICS: a General Interface Layer to Integrate Logic Inference and Deep Learning⋆ Inproceedings
In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML, 2019.
Learning Activation Functions by Means of Kernel Based Neural Networks Inproceedings
In: International Conference of the Italian Association for Artificial Intelligence, pp. 418–430, Springer, Cham 2019.
T-Norms Driven Loss Functions for Machine Learning Journal Article
In: arXiv preprint arXiv:1907.11468, 2019.
2018
Backpropagation and biological plausibility Journal Article
In: arXiv preprint arXiv:1808.06934, 2018.
An unsupervised character-aware neural approach to word and context representation learning Inproceedings
In: International Conference on Artificial Neural Networks, pp. 126–136, Springer, Cham 2018.
A Constrained-Based Approach to Machine Learning Inproceedings
In: 2018 14th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), pp. 737–746, IEEE 2018.
2016
Information diffusion in a multi-social-network scenario: framework and ASP-based analysis Journal Article
In: Knowledge and Information Systems, vol. 48, no. 3, pp. 619–648, 2016.
2014
Investigating information diffusion in a multi-social-network scenario via answer set programming Inproceedings
In: International Conference on Web Reasoning and Rule Systems, pp. 191–196, Springer, Cham 2014.
Exploiting answer set programming for handling information diffusion in a multi-social-network scenario Inproceedings
In: European Workshop on Logics in Artificial Intelligence, pp. 618–627, Springer, Cham 2014.
Investigating Node Influence Maximization and Influential Node Characterization in a Multi-Social-Network Scenario via Disjunctive Logic Programming. Inproceedings
In: SEBD, pp. 264–275, 2014.
Defining and investigating the scope of users and hashtags in Twitter Inproceedings
In: OTM Confederated International Conferences" On the Move to Meaningful Internet Systems", pp. 674–681, Springer, Berlin, Heidelberg 2014.
An approach to handling Information Diffusion problem in a Multi-Social-Network Scenario PhD Thesis
Universit`a degli Studi Mediterranea di Reggio Calabria, 2014.
0000
Deep Lagrangian Propagation in Graph Neural Networks Journal Article
In: 0000.
Tensorised Probabilistic Inference for Neural Probabilistic Logic Programming Inproceedings
In: The 5th Workshop on Tractable Probabilistic Modeling, 0000.
Learning to Generate Molecules From Small Datasets Using Neural Markov Logic Networks Journal Article
In: 0000.