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Riccardo Taormina

Showing results (1-10 of 10) with videos related to

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Water Research|July 7, 2024
Towards transferable metamodels for water distribution systems with edge-based graph neural networksBulat Kerimov, Riccardo Taormina, Franz Tscheikner-Gratl
Water Research|September 14, 2024
Transferable and data efficient metamodeling of storm water system nodal depths using auto-regressive graph neural networksAlexander Garzón, Zoran Kapelan, Jeroen Langeveld, et al.
Water Research|December 12, 2025
Evaluation of graph neural networks for urban drainage metamodeling: Key components and transferability analysisAlexander Garzón, Zoran Kapelan, Jeroen Langeveld, et al.
Water Research|January 11, 2025
State estimation in water distribution system via diffusion on the edge spaceBulat Kerimov, Maosheng Yang, Riccardo Taormina, et al.
IEEE Transactions on Cybernetics|July 8, 2015
Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy ApproachGulsah Karakaya, Stefano Galelli, Selin Damla Ahipasaoglu, et al.
Journal of Chemical Information and Modeling|June 26, 2026
Evaluating Molecular Representations for Predicting Cyclodextrin-PFAS Binding Energy with Machine Learning: Domain Transfer and Data LimitationsCole Brzakala, Othonas A Moultos, Jan Peter van der Hoek, et al.
Water Research|September 12, 2024
Detecting floating litter in freshwater bodies with semi-supervised deep learningTianlong Jia, Rinze de Vries, Zoran Kapelan, et al.
Water Research|January 23, 2023
Deep learning for detecting macroplastic litter in water bodies: A reviewTianlong Jia, Zoran Kapelan, Rinze de Vries, et al.
Water Research|October 29, 2025
A semi-supervised learning-based framework for quantifying litter fluxes in river systemsTianlong Jia, Riccardo Taormina, Rinze de Vries, et al.
Iscience|June 17, 2026
Exploring transferability of plastic-water hyacinth interaction and detection in riversGiel W A Hagenbeek, Tim H M van Emmerik, Tianlong Jia, et al.
Pageof 1

Showing results (1-10 of 10) with videos related to

Sort By:
Pageof 1
Water Research|July 7, 2024
Towards transferable metamodels for water distribution systems with edge-based graph neural networksBulat Kerimov, Riccardo Taormina, Franz Tscheikner-Gratl
Water Research|September 14, 2024
Transferable and data efficient metamodeling of storm water system nodal depths using auto-regressive graph neural networksAlexander Garzón, Zoran Kapelan, Jeroen Langeveld, et al.
Water Research|December 12, 2025
Evaluation of graph neural networks for urban drainage metamodeling: Key components and transferability analysisAlexander Garzón, Zoran Kapelan, Jeroen Langeveld, et al.
Water Research|January 11, 2025
State estimation in water distribution system via diffusion on the edge spaceBulat Kerimov, Maosheng Yang, Riccardo Taormina, et al.
IEEE Transactions on Cybernetics|July 8, 2015
Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy ApproachGulsah Karakaya, Stefano Galelli, Selin Damla Ahipasaoglu, et al.
Journal of Chemical Information and Modeling|June 26, 2026
Evaluating Molecular Representations for Predicting Cyclodextrin-PFAS Binding Energy with Machine Learning: Domain Transfer and Data LimitationsCole Brzakala, Othonas A Moultos, Jan Peter van der Hoek, et al.
Water Research|September 12, 2024
Detecting floating litter in freshwater bodies with semi-supervised deep learningTianlong Jia, Rinze de Vries, Zoran Kapelan, et al.
Water Research|January 23, 2023
Deep learning for detecting macroplastic litter in water bodies: A reviewTianlong Jia, Zoran Kapelan, Rinze de Vries, et al.
Water Research|October 29, 2025
A semi-supervised learning-based framework for quantifying litter fluxes in river systemsTianlong Jia, Riccardo Taormina, Rinze de Vries, et al.
Iscience|June 17, 2026
Exploring transferability of plastic-water hyacinth interaction and detection in riversGiel W A Hagenbeek, Tim H M van Emmerik, Tianlong Jia, et al.
Pageof 1