Ivan Diliso

According to our database, Ivan Diliso authored at least 21 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Return of the Schema: Building Complete Datasets for Machine Learning and Reasoning on Knowledge Graphs.

Ivan Diliso, Roberto Barile, Claudia d'Amato, Nicola Fanizzi

CoRR, February, 2026

2025

KG-SaF: Building Complete and Curated Datasets for Machine Learning and Reasoning on Knowledge Graphs.

Ivan Diliso, Roberto Barile, Claudia d'Amato, Nicola Fanizzi

Dataset, December, 2025

KG-SaF: Building Complete and Curated Datasets for Machine Learning and Reasoning on Knowledge Graphs.

Ivan Diliso, Roberto Barile, Claudia d'Amato, Nicola Fanizzi

Dataset, December, 2025

KG-SaF: Building Complete and Curated Datasets for Machine Learning and Reasoning on Knowledge Graphs.

Ivan Diliso, Roberto Barile, Claudia d'Amato, Nicola Fanizzi

Dataset, December, 2025

KG-SaF: Building Complete and Curated Datasets for Machine Learning and Reasoning on Knowledge Graphs.

Ivan Diliso, Roberto Barile, Claudia d'Amato, Nicola Fanizzi

Dataset, December, 2025

KG-SaF: Building Complete and Curated Datasets for Machine Learning and Reasoning on Knowledge Graphs.

Ivan Diliso, Roberto Barile, Claudia d'Amato, Nicola Fanizzi

Dataset, December, 2025

KG-SaF: Building Complete and Curated Datasets for Machine Learning and Reasoning on Knowledge Graphs.

Ivan Diliso, Roberto Barile, Claudia d'Amato, Nicola Fanizzi

Dataset, December, 2025

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models.

Claudia d'Amato, Ivan Diliso, Nicola Fanizzi, Zafar Saeed

CoRR, August, 2025

Learning Interpretable Probabilistic Models and Schema Axioms for Knowledge Graphs.

Ivan Diliso, Nicola Fanizzi, Claudia d'Amato

Dataset, August, 2025

Learning Interpretable Probabilistic Models and Schema Axioms for Knowledge Graphs.

Ivan Diliso, Nicola Fanizzi, Claudia d'Amato

Dataset, June, 2025

Learning Interpretable Probabilistic Models and Schema Axioms for Knowledge Graphs.

Ivan Diliso, Nicola Fanizzi, Claudia d'Amato

Dataset, June, 2025

Learning Interpretable Probabilistic Models and Schema Axioms for Knowledge Graphs.

Ivan Diliso, Nicola Fanizzi, Claudia d'Amato

Dataset, June, 2025

Learning Interpretable Probabilistic Models and Schema Axioms for Knowledge Graphs.

Ivan Diliso, Nicola Fanizzi, Claudia d'Amato

Dataset, June, 2025

Learning Interpretable Probabilistic Models and Schema Axioms for Knowledge Graphs.

Ivan Diliso, Nicola Fanizzi, Claudia d'Amato

Dataset, June, 2025

Learning Interpretable Probabilistic Models and Schema Axioms for Knowledge Graphs.

Ivan Diliso, Nicola Fanizzi, Claudia d'Amato

Dataset, June, 2025

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models.

Claudia d'Amato, Ivan Diliso, Nicola Fanizzi, Zafar Saeed

Dataset, May, 2025

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models.

Claudia d'Amato, Ivan Diliso, Nicola Fanizzi, Zafar Saeed

Dataset, May, 2025

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models.

Claudia d'Amato, Ivan Diliso, Nicola Fanizzi, Zafar Saeed

Dataset, May, 2025

Learning Interpretable Probabilistic Models and Schema Axioms for Knowledge Graphs.

Ivan Diliso, Nicola Fanizzi, Claudia d'Amato

Proceedings of the Rules and Reasoning - 9th International Joint Conference, 2025

Towards Semantically Enriched Knowledge Graph Embedding through Ontology Axiom Integration.

Ivan Diliso

Proceedings of the Companion Proceedings of the 9th International Joint Conference on Rules and Reasoning, 2025

2023

A Hybrid Quantum-Classical Framework for Binary Classification in Online Learning.

Corrado Loglisci, Ivan Diliso, Donato Malerba

Proceedings of the 31st Symposium of Advanced Database Systems, 2023