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08/23/2023
Relational Concept Based Models
The design of interpretable deep learning models working in relational d...
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07/01/2023
SHARCS: Shared Concept Space for Explainable Multimodal Learning
Multimodal learning is an essential paradigm for addressing complex real...
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04/27/2023
Categorical Foundations of Explainable AI
Explainable AI (XAI) aims to address the human need for safe and reliabl...
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04/27/2023
Interpretable Neural-Symbolic Concept Reasoning
Deep learning methods are highly accurate, yet their opaque decision pro...
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02/09/2023
GCI: A (G)raph (C)oncept (I)nterpretation Framework
Explainable AI (XAI) underwent a recent surge in research on concept ext...
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01/25/2023
Towards Robust Metrics for Concept Representation Evaluation
Recent work on interpretability has focused on concept-based explanation...
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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...
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09/19/2022
Concept Embedding Models
Deploying AI-powered systems requires trustworthy models supporting effe...
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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-...
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07/27/2022
Encoding Concepts in Graph Neural Networks
The opaque reasoning of Graph Neural Networks induces a lack of human tr...
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08/11/2021
Logic Explained Networks
The large and still increasing popularity of deep learning clashes with ...
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07/15/2021
Algorithmic Concept-based Explainable Reasoning
Recent research on graph neural network (GNN) models successfully applie...
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06/12/2021
Entropy-based Logic Explanations of Neural Networks
Explainable artificial intelligence has rapidly emerged since lawmakers ...
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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...
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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...
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09/06/2020
Gradient-based Competitive Learning: Theory
Deep learning has been widely used for supervised learning and classific...
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08/21/2020
Topological Gradient-based Competitive Learning
Topological learning is a wide research area aiming at uncovering the mu...
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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...
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06/09/2020
The Computational Patient has Diabetes and a COVID
Medicine is moving from a curative discipline to a preventative discipli...
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02/20/2020