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2020 – today
- 2024
[j4]Matteo Terzi, Mattia Carletti
, Gian Antonio Susto:
Improving robustness with image filtering. Neurocomputing 596: 127927 (2024)- [j3]Mattia Carletti, Alberto Sinigaglia, Matteo Terzi, Gian Antonio Susto:
On the limitations of adversarial training for robust image classification with convolutional neural networks. Inf. Sci. 675: 120703 (2024) - 2023
- [j2]Mattia Carletti, Matteo Terzi, Gian Antonio Susto:
Interpretable Anomaly Detection with DIFFI: Depth-based feature importance of Isolation Forest. Eng. Appl. Artif. Intell. 119: 105730 (2023) - [j1]David Dandolo, Chiara Masiero, Mattia Carletti, Davide Dalle Pezze, Gian Antonio Susto:
AcME - Accelerated model-agnostic explanations: Fast whitening of the machine-learning black box. Expert Syst. Appl. 214: 119115 (2023) - 2022
- [i5]Mattia Carletti, Matteo Terzi, Gian Antonio Susto:
On the Properties of Adversarially-Trained CNNs. CoRR abs/2203.09243 (2022) - 2021
- [c4]Alessandro Fabris, Alan Mishler, Stefano Gottardi, Mattia Carletti, Matteo Daicampi, Gian Antonio Susto, Gianmaria Silvello:
Algorithmic Audit of Italian Car Insurance: Evidence of Unfairness in Access and Pricing. AIES 2021: 458-468 - [i4]Alessandro Fabris, Alan Mishler, Stefano Gottardi, Mattia Carletti, Matteo Daicampi, Gian Antonio Susto, Gianmaria Silvello:
Algorithmic Audit of Italian Car Insurance: Evidence of Unfairness in Access and Pricing. CoRR abs/2105.10174 (2021) - [i3]Matteo Terzi, Mattia Carletti, Gian Antonio Susto:
Improving Robustness with Image Filtering. CoRR abs/2112.11235 (2021) - [i2]David Dandolo, Chiara Masiero, Mattia Carletti, Davide Dalle Pezze, Gian Antonio Susto:
AcME - Accelerated Model-agnostic Explanations: Fast Whitening of the Machine-Learning Black Box. CoRR abs/2112.12635 (2021) - 2020
- [c3]Mattia Carletti, Marco Maggipinto, Alessandro Beghi, Gian Antonio Susto, Natalie Gentner, Yao Yang, Andreas Kyek:
Interpretable Anomaly Detection for Knowledge Discovery in Semiconductor Manufacturing. WSC 2020: 1875-1885 - [c2]Natalie Gentner, Andreas Kyek, Yao Yang, Mattia Carletti, Gian Antonio Susto:
Enhancing Scalability of Virtual Metrology: A Deep Learning-Based Approach for Domain Adaptation. WSC 2020: 1898-1909 - [i1]Mattia Carletti, Matteo Terzi, Gian Antonio Susto:
Interpretable Anomaly Detection with DIFFI: Depth-based Feature Importance for the Isolation Forest. CoRR abs/2007.11117 (2020)
2010 – 2019
- 2019
- [c1]Mattia Carletti, Chiara Masiero, Alessandro Beghi, Gian Antonio Susto:
Explainable Machine Learning in Industry 4.0: Evaluating Feature Importance in Anomaly Detection to Enable Root Cause Analysis. SMC 2019: 21-26
Coauthor Index
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