36 citations · 115 across the 16 of their papers we have counts for
7 papers · 1 filter
DeepProofLog: Efficient Proving in Deep Stochastic Logic Programs
Ying Jiao, Rodrigo Castellano Ontiveros, Luc De Raedt +4
Neurosymbolic (NeSy) AI aims to combine the strengths of neural architectures and symbolic reasoning to improve the accuracy, interpretability, and generalization capability of AI…
Grounding Methods for Neural-Symbolic AI
Rodrigo Castellano Ontiveros, Francesco Giannini, Marco Gori +2
A large class of Neural-Symbolic (NeSy) methods employs a machine learner to process the input entities, while relying on a reasoner based on First-Order Logic to represent and pro…
Interpretable Concept-Based Memory Reasoning
David Debot, Pietro Barbiero, Francesco Giannini +3
The lack of transparency in the decision-making processes of deep learning systems presents a significant challenge in modern artificial intelligence (AI), as it impairs users' abi…
Enhancing Embedding Representations of Biomedical Data using Logic Knowledge
Michelangelo Diligenti, Francesco Giannini, Stefano Fioravanti +3
Knowledge Graph Embeddings (KGE) have become a quite popular class of models specifically devised to deal with ontologies and graph structure data, as they can implicitly encode st…
Relational Reasoning Networks
Giuseppe Marra, Michelangelo Diligenti, Francesco Giannini
Neuro-symbolic methods integrate neural architectures, knowledge representation and reasoning. However, they have been struggling at both dealing with the intrinsic uncertainty of…
Relational Neural Machines
Giuseppe Marra, Michelangelo Diligenti, Francesco Giannini +2
Deep learning has been shown to achieve impressive results in several tasks where a large amount of training data is available. However, deep learning solely focuses on the accurac…
T-Norms Driven Loss Functions for Machine Learning
Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti +2
Neural-symbolic approaches have recently gained popularity to inject prior knowledge into a learner without requiring it to induce this knowledge from data. These approaches can po…