Følg
Danny D'Agostino
Danny D'Agostino
Research Fellow, Centre for Quantitative Medicine, Duke-NUS Medical School
Verifisert e-postadresse på nus.edu.sg - Startside
Tittel
Sitert av
Sitert av
År
Nonlinear methods for design-space dimensionality reduction in shape optimization
D D’Agostino, A Serani, EF Campana, M Diez
Machine Learning, Optimization, and Big Data: Third International Conference …, 2018
412018
Design-space assessment and dimensionality reduction: An off-line method for shape reparameterization in simulation-based optimization
D D’Agostino, A Serani, M Diez
Ocean Engineering 197, 106852, 2020
402020
Deep autoencoder for off-line design-space dimensionality reduction in shape optimization
D D'Agostino, A Serani, EF Campana, M Diez
2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials …, 2018
35*2018
Recurrent-type neural networks for real-time short-term prediction of ship motions in high sea state
D D'Agostino, A Serani, F Stern, M Diez
arXiv preprint arXiv:2105.13102, 2021
162021
Assessing the interplay of shape and physical parameters by unsupervised nonlinear dimensionality reduction methods
A Serani, D D'Agostino, EF Campana, M Diez
Journal of Ship Research 64 (04), 313-327, 2020
152020
Time-series forecasting for ships maneuvering in waves via recurrent-type neural networks
D D’Agostino, A Serani, F Stern, M Diez
Journal of Ocean Engineering and Marine Energy 8 (4), 479-487, 2022
112022
Assessing the interplay of shape and physical parameters by nonlinear dimensionality reduction methods
A Serani, D D’Agostino, EF Campana, M Diez
Proceedings of the 32st Symposium on Naval Hydrodynamics, Hamburg, Germany, 2018
102018
On the combined effect of design-space dimensionality reduction and optimization methods on shape optimization efficiency
D D'Agostino, A Serani, M Diez
2018 Multidisciplinary Analysis and Optimization Conference, 4058, 2018
92018
Augmented design-space exploration by nonlinear dimensionality reduction methods
D D’Agostino, A Serani, EF Campana, M Diez
Machine Learning, Optimization, and Data Science: 4th International …, 2019
52019
PIV data clustering of a buoyant jet in a stratified environment
A Serani, D Durante, M Diez, D D'Agostino, S Clement, J Badra, M Andre, ...
AIAA Scitech 2019 Forum, 1830, 2019
52019
Observing PIV Measurements Through the Lens of Data Clustering
D D’Agostino, M Andre, P Bardet, A Serani, M Felli, M Diez
Proceedings of the 33rd Symposium on Naval Hydrodynamics, Osaka, Japan, 18-23, 2020
42020
PIV Snapshot Clustering Reveals the Dual Deterministic and Chaotic Nature of Propeller Wakes at Macro-and Micro-Scales
D D’Agostino, M Diez, M Felli, A Serani
Journal of Marine Science and Engineering 11 (6), 1220, 2023
22023
An Efficient Global Optimization Algorithm with Adaptive Estimates of the Local Lipschitz Constants
D D'Agostino
arXiv preprint arXiv:2211.04129, 2022
22022
Learning Active Subspaces and Discovering Important Features with Gaussian Radial Basis Functions Neural Networks
D D'Agostino, I Ilievski, CA Shoemaker
arXiv preprint arXiv:2307.05639, 2023
12023
Generative models for anomaly detection and design-space dimensionality reduction in shape optimization
D D’Agostino
Engineering Applications of Artificial Intelligence 129, 107566, 2024
2024
Federated Learning for Clinical Structured Data: A Benchmark Comparison of Engineering and Statistical Approaches
S Li, D Miao, Q Wu, C Hong, D D'Agostino, X Li, Y Ning, Y Shang, H Fu, ...
arXiv preprint arXiv:2311.03417, 2023
2023
Systemet kan ikke utføre handlingen. Prøv på nytt senere.
Artikler 1–16