Biagio La Rosa

According to our database, Biagio La Rosa authored at least 10 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Prototype-Based Interpretable Graph Neural Networks.

Alessio Ragno, Biagio La Rosa, Roberto Capobianco

IEEE Trans. Artif. Intell., April, 2024

Explainable AI in drug discovery: self-interpretable graph neural network for molecular property prediction using concept whitening.

Michela Proietti, Alessio Ragno, Biagio La Rosa, Rino Ragno, Roberto Capobianco

Mach. Learn., April, 2024

Explaining Deep Neural Networks by Leveraging Intrinsic Methods.

Biagio La Rosa

CoRR, 2024

2023

A self-interpretable module for deep image classification on small data.

Biagio La Rosa, Roberto Capobianco, Daniele Nardi

Appl. Intell., April, 2023

State of the Art of Visual Analytics for eXplainable Deep Learning.

Biagio La Rosa, Graziano Blasilli, Romain Bourqui, David Auber, Giuseppe Santucci, Roberto Capobianco, Enrico Bertini, Romain Giot, Marco Angelini

Comput. Graph. Forum, February, 2023

Towards a fuller understanding of neurons with Clustered Compositional Explanations.

Biagio La Rosa, Leilani Gilpin, Roberto Capobianco

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2021

Memory Wrap: a Data-Efficient and Interpretable Extension to Image Classification Models.

Biagio La Rosa, Roberto Capobianco, Daniele Nardi

CoRR, 2021

A Discussion about Explainable Inference on Sequential Data via Memory-Tracking.

Biagio La Rosa, Roberto Capobianco, Daniele Nardi

Proceedings of the AIxIA 2021 Discussion Papers co-located with the the 20th International Conference of the Italian Association for Artificial Intelligence (AIxIA2021), 2021

Detection Accuracy for Evaluating Compositional Explanations of Units.

Sayo M. Makinwa, Biagio La Rosa, Roberto Capobianco

Proceedings of the AIxIA 2021 - Advances in Artificial Intelligence, 2021

2020

Explainable Inference on Sequential Data via Memory-Tracking.

Biagio La Rosa, Roberto Capobianco, Daniele Nardi

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020