Marco Maggipinto
Marco Maggipinto
Ph.D student, University of Padua
Verified email at
Cited by
Cited by
A Convolutional Autoencoder Approach for Feature Extraction in Virtual Metrology
M Maggipinto, C Masiero, A Beghi, GA Susto
Procedia Manufacturing 17, 126-133, 2018
A computer vision-inspired deep learning architecture for virtual metrology modeling with 2-dimensional data
M Maggipinto, M Terzi, C Masiero, A Beghi, GA Susto
IEEE Transactions on Semiconductor Manufacturing 31 (3), 376-384, 2018
DeepVM: A Deep Learning-based approach with automatic feature extraction for 2D input data Virtual Metrology
M Maggipinto, A Beghi, S McLoone, GA Susto
Journal of Process Control 84, 24-34, 2019
Deep learning for virtual metrology: Modeling with optical emission spectroscopy data
M Terzi, C Masiero, A Beghi, M Maggipinto, GA Susto
2017 IEEE 3rd International Forum on Research and Technologies for Society …, 2017
Adversarial training reduces information and improves transferability
M Terzi, A Achille, M Maggipinto, GA Susto
AAAI, 2020, 2020
Machine Learning-based laundry weight estimation for vertical axis washing machines
GA Susto, M Maggipinto, G Zannon, F Altinier, E Pesavento, A Beghi
2018 European Control Conference (ECC), 3179-3184, 2018
Probabilistic word embeddings in neural IR: A Promising model that does not work as expected (for now)
A Purpura, M Maggipinto, G Silvello, GA Susto
Proceedings of the 2019 ACM SIGIR International Conference on Theory of …, 2019
Laundry fabric classification in vertical axis washing machines using data-driven soft sensors
M Maggipinto, E Pesavento, F Altinier, G Zambonin, A Beghi, GA Susto
Energies 12 (21), 4080, 2019
Induced start dynamic sampling for wafer metrology optimization
GA Susto, M Maggipinto, F Zocco, S McLoone
IEEE Transactions on Automation Science and Engineering 17 (1), 418-432, 2019
A Dynamic Sampling Approach for Cost Reduction in Semiconductor Manufacturing
GA Susto, M Maggipinto, F Zocco, S McLoone
Procedia Manufacturing 17, 1031-1038, 2018
On optimising spatial sampling plans for wafer profile reconstruction
S McLoone, F Zocco, M Maggipinto, GA Susto
IFAC-PapersOnLine 51 (10), 115-120, 2018
β-Variational Classifiers Under Attack
M Maggipinto, M Terzi, GA Susto
IFAC-PapersOnLine 53 (2), 7903-7908, 2020
A Deep Learning-based Approach to Anomaly Detection with 2-Dimensional Data in Manufacturing
M Maggipinto, A Beghi, GA Susto
2019 IEEE 17th International Conference on Industrial Informatics (INDIN) 1 …, 2019
Exploiting 2D Coordinates as Bayesian Priors for Deep Learning Defect Classification of SEM Images
S Arena, Y Budrov, M Carletti, N Gentner, M Maggipinto, Y Yang, A Beghi, ...
IEEE Transactions on Semiconductor Manufacturing, 2021
Greedy Search Algorithms for Unsupervised Variable Selection: A Comparative Study
F Zocco, M Maggipinto, GA Susto, S McLoone
arXiv preprint arXiv:2103.02687, 2021
Interpretable anomaly detection for knowledge discovery in semiconductor manufacturing
M Carletti, M Maggipinto, A Beghi, GA Susto, N Gentner, Y Yang, A Kyek
2020 Winter Simulation Conference (WSC), 1875-1885, 2020
IntroVAC: Introspective Variational Classifiers for Learning Interpretable Latent Subspaces
M Maggipinto, M Terzi, GA Susto
arXiv preprint arXiv:2008.00760, 2020
Proximal Deterministic Policy Gradient
M Maggipinto, GA Susto, P Chaudhari
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020
What are the Most Informative Data for Virtual Metrology? A use case on Multi-Stage Processes Fault Prediction
M Maggipinto, GA Susto, F Zocco, S McLoone
2019 IEEE 15th International Conference on Automation Science and …, 2019
The system can't perform the operation now. Try again later.
Articles 1–19