@article {11573/1693393,
	title = {{Artificial neural networks exploiting point cloud data for fragmented solid objects classification}},
	journal = {MACHINE LEARNING: SCIENCE AND TECHNOLOGY},
	volume = {{4}},
	number = {{4}},
	year = {2023},
	pages = {False-False},
	keywords = {DGCNN, fragments of artifacts, Graph neural network, point clouds, PointNet, solid objects dataset}, {classification},
	doi = {{10.1088/2632-2153/ad035e}},
	author = {Baiocchi, A. and Giagu, S. and Napoli, C. and Serra, M. and Nardelli, P. and Valleriani, M.}
}
@article {11573/1686452,
	title = {{Convergent Approaches to AI Explainability for HEP Muonic Particles Pattern Recognition}},
	journal = {COMPUTING AND SOFTWARE FOR BIG SCIENCE},
	volume = {{7}},
	number = {{1}},
	year = {2023},
	pages = {False-False},
	keywords = {High-energy physics, Intrinsically interpretable Decision Trees, Saliency maps methods, Tracing gradient descent}, {Explainable Artificial Intelligence},
	doi = {{10.1007/s41781-023-00102-z}},
	author = {Maglianella, L. and Nicoletti, L. and Giagu, S. and Napoli, C. and Scardapane, S.}
}
@article {11573/1686452,
	title = {{Convergent Approaches to AI Explainability for HEP Muonic Particles Pattern Recognition}},
	journal = {COMPUTING AND SOFTWARE FOR BIG SCIENCE},
	volume = {{7}},
	number = {{1}},
	year = {2023},
	pages = {False-False},
	keywords = {High-energy physics, Intrinsically interpretable Decision Trees, Saliency maps methods, Tracing gradient descent}, {Explainable Artificial Intelligence},
	doi = {{10.1007/s41781-023-00102-z}},
	author = {Maglianella, L. and Nicoletti, L. and Giagu, S. and Napoli, C. and Scardapane, S.}
}
