Gabriele Ciravegna | DeepAI

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∙ 08/23/2023

Relational Concept Based Models

The design of interpretable deep learning models working in relational d...

0 Pietro Barbiero, et al. ∙

∙ 04/27/2023

Interpretable Neural-Symbolic Concept Reasoning

Deep learning methods are highly accurate, yet their opaque decision pro...

0 Pietro Barbiero, et al. ∙

∙ 09/19/2022

Concept Embedding Models

Deploying AI-powered systems requires trustworthy models supporting effe...

0 Mateo Espinosa Zarlenga, et al. ∙

∙ 07/27/2022

Encoding Concepts in Graph Neural Networks

The opaque reasoning of Graph Neural Networks induces a lack of human tr...

0 Lucie Charlotte Magister, et al. ∙

∙ 10/15/2021

Knowledge-driven Active Learning

In the last few years, Deep Learning models have become increasingly pop...

0 Gabriele Ciravegna, et al. ∙

∙ 09/21/2021

Graph Neural Networks for Graph Drawing

Graph Drawing techniques have been developed in the last few years with ...

5 Matteo Tiezzi, et al. ∙

∙ 08/11/2021

Logic Explained Networks

The large and still increasing popularity of deep learning clashes with ...

12 Gabriele Ciravegna, et al. ∙

∙ 06/12/2021

Entropy-based Logic Explanations of Neural Networks

Explainable artificial intelligence has rapidly emerged since lawmakers ...

0 Pietro Barbiero, et al. ∙

∙ 05/25/2021

LENs: a Python library for Logic Explained Networks

LENs is a Python module integrating a variety of state-of-the-art approa...

0 Pietro Barbiero, et al. ∙

∙ 09/06/2020

Gradient-based Competitive Learning: Theory

Deep learning has been widely used for supervised learning and classific...

0 Giansalvo Cirrincione, et al. ∙

∙ 08/21/2020

Topological Gradient-based Competitive Learning

Topological learning is a wide research area aiming at uncovering the mu...

0 Pietro Barbiero, et al. ∙

∙ 06/06/2020

Can Domain Knowledge Alleviate Adversarial Attacks in Multi-Label Classifiers?

Adversarial attacks on machine learning-based classifiers, along with de...

16 Stefano Melacci, et al. ∙

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