Nonlinear Methods for Design-Space Dimensionality Reduction in Shape Optimization. - Danny D'Agostino; Andrea Serani; Emilio Fortunato Campana; Matteo Diez (MOD, 2017)

Augmented Design-Space Exploration by Nonlinear Dimensionality Reduction Methods. - Danny D'Agostino; Andrea Serani; Emilio Fortunato Campana; Matteo Diez (LOD, 2018)

Recurrent-type Neural Networks for Real-time Short-term Prediction of Ship Motions in High Sea State. - Danny D'Agostino; Andrea Serani; Frederick Stern; Matteo Diez (CoRR, 2021)

A lipschitzian global optimization algorithm and machine learning for fluid dynamics. - Danny D'Agostino (2021)

Federated Learning for Clinical Structured Data: A Benchmark Comparison of Engineering and Statistical Approaches. - Siqi Li 004; Di Miao; Qiming Wu 001; Chuan Hong; Danny D'Agostino; Xin Li 079; Yilin Ning; Yuqing Shang; Huazhu Fu; Marcus Eng Hock Ong; Hamed Haddadi; Nan Liu 003 (CoRR, 2023)

Bridging Data Gaps in Healthcare: A Scoping Review of Transfer Learning in Biomedical Data Analysis. - Siqi Li 004; Xin Li 079; Kunyu Yu; Di Miao; Mingcheng Zhu 003; Mengying Yan; Yuhe Ke; Danny D'Agostino; Yilin Ning; Qiming Wu 001; Ziwen Wang; Yuqing Shang; et al. (CoRR, 2024)

Generative models for anomaly detection and design-space dimensionality reduction in shape optimization. - Danny D'Agostino (Eng. Appl. Artif. Intell., 2024)

Learning active subspaces and discovering important features with Gaussian radial basis functions neural networks. - Danny D'Agostino; Ilija Ilievski; Christine Annette Shoemaker (Neural Networks, 2024)

Disparities in clinical studies of AI enabled applications from a global perspective. - Rui Yang; Sabarinath Vinod Nair; Yuhe Ke; Danny D'Agostino; Mingxuan Liu; Yilin Ning; Nan Liu 003 (npj Digit. Medicine, 2024)