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A Revised Isolation Forest procedure for Anomaly Detection with High Number of Data Points.

E. Marcelli, T. Barbariol, V. Savarino, A. Beghi, and G. Susto. LATS, page 1-5. IEEE, (2022)

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Gian Antonio d' Addetta

Gian Töndury

Gian Brändli

Gian Schmid

Gian Martin

Other publications of authors with the same name

Dealing with time-series data in Predictive Maintenance problems.G. Susto, and A. Beghi. ETFA, page 1-4. IEEE, (2016)Human Activity Recognition with Wearable Devices: A Symbolic Approach.A. Cenedese, L. Minetto, G. Susto, and M. Terzi. PsychNology J., 14 (2-3): 33-65 (2016)Fault Detection of Bearing: An Unsupervised Machine Learning Approach Exploiting Feature Extraction and Dimensionality Reduction.L. Brito, G. Susto, J. Brito, and M. Duarte. Informatics, 8 (4): 85 (2021)Machine Learning for Predictive Maintenance: A Multiple Classifier Approach.G. Susto, A. Schirru, S. Pampuri, S. McLoone, and A. Beghi. IEEE Trans. Ind. Informatics, 11 (3): 812-820 (2015)AcME - Accelerated Model-agnostic Explanations: Fast Whitening of the Machine-Learning Black Box.D. Dandolo, C. Masiero, M. Carletti, D. Pezze, and G. Susto. CoRR, (2021)Directional adversarial training for cost sensitive deep learning classification applications.M. Terzi, G. Susto, and P. Chaudhari. Eng. Appl. Artif. Intell., (2020)Bayesian Deep Learning for Remaining Useful Life Estimation via Stein Variational Gradient Descent.L. Libera, J. Andreoli, D. Pezze, M. Ravanelli, and G. Susto. CoRR, (2024)Instagram Images and Videos Popularity Prediction: a Deep Learning-Based Approach.L. Brunelli, M. Viola, and G. Susto. AIABI@AI*IA, volume 3102 of CEUR Workshop Proceedings, CEUR-WS.org, (2021)Predictive Maintenance in the Industry: A Comparative Study on Deep Learning-based Remaining Useful Life Estimation.L. Lorenti, D. Pezze, J. Andreoli, C. Masiero, N. Gentner, Y. Yang, and G. Susto. INDIN, page 1-9. IEEE, (2023)Explainable Machine Learning in Industry 4.0: Evaluating Feature Importance in Anomaly Detection to Enable Root Cause Analysis.M. Carletti, C. Masiero, A. Beghi, and G. Susto. SMC, page 21-26. IEEE, (2019)

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Disambiguation of "Susto, Gian Antonio"

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A Revised Isolation Forest procedure for Anomaly Detection with High Number of Data Points.

Please choose a person to relate this publication to

Gian Antonio d' Addetta

Gian Töndury

Gian Brändli

Gian Schmid

Gian Martin

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Susto, Gian Antonio"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML A Revised Isolation Forest procedure for Anomaly Detection with High Number of Data Points.

Please choose a person to relate this publication to

Gian Antonio d' Addetta

Gian Töndury

Gian Brändli

Gian Schmid

Gian Martin

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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MSOffice XML

A Revised Isolation Forest procedure for Anomaly Detection with High Number of Data Points.