Pietro Barbiero | 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. ∙

∙ 07/01/2023

SHARCS: Shared Concept Space for Explainable Multimodal Learning

Multimodal learning is an essential paradigm for addressing complex real...

0 Gabriele Dominici, et al. ∙

∙ 04/27/2023

Categorical Foundations of Explainable AI

Explainable AI (XAI) aims to address the human need for safe and reliabl...

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. ∙

∙ 02/09/2023

GCI: A (G)raph (C)oncept (I)nterpretation Framework

Explainable AI (XAI) underwent a recent surge in research on concept ext...

7 Dmitry Kazhdan, et al. ∙

∙ 01/25/2023

Towards Robust Metrics for Concept Representation Evaluation

Recent work on interpretability has focused on concept-based explanation...

0 Mateo Espinosa Zarlenga, et al. ∙

∙ 10/13/2022

Global Explainability of GNNs via Logic Combination of Learned Concepts

While instance-level explanation of GNN is a well-studied problem with p...

0 Steve Azzolin, et al. ∙

∙ 09/19/2022

Concept Embedding Models

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

0 Mateo Espinosa Zarlenga, et al. ∙

∙ 08/22/2022

Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis

Graph neural networks (GNNs) are highly effective on a variety of graph-...

0 Han Xuanyuan, 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. ∙

∙ 08/11/2021

Logic Explained Networks

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

12 Gabriele Ciravegna, et al. ∙

∙ 07/15/2021

Algorithmic Concept-based Explainable Reasoning

Recent research on graph neural network (GNN) models successfully applie...

0 Dobrik Georgiev, 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. ∙

∙ 09/17/2020

Graph representation forecasting of patient's medical conditions: towards a digital twin

Objective: Modern medicine needs to shift from a wait and react, curativ...

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. ∙

∙ 06/28/2020

Modeling Generalization in Machine Learning: A Methodological and Computational Study

As machine learning becomes more and more available to the general publi...

0 Pietro Barbiero, et al. ∙

∙ 06/09/2020

The Computational Patient has Diabetes and a COVID

Medicine is moving from a curative discipline to a preventative discipli...

0 Pietro Barbiero, et al. ∙

∙ 02/20/2020

Uncovering Coresets for Classification With Multi-Objective Evolutionary Algorithms

A coreset is a subset of the training set, using which a machine learnin...

0 Pietro Barbiero, et al. ∙

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