2 citations · 5 across the 3 of their papers we have counts for
3 papers
Hierarchical Higher-Order Dynamic Mode Decomposition for Clustering and Feature Selection
Adrián Corrochano, Giuseppe D'Alessio, Alessandro Parente +1
In this work, a new algorithm based on the application of higher-order dynamic mode decomposition (HODMD) is proposed for feature selection and variables clustering in reacting flo…
A predictive physics-aware hybrid reduced order model for reacting flows
Adrián Corrochano, Rodolfo S. M. Freitas, Alessandro Parente +1
In this work, a new hybrid predictive Reduced Order Model (ROM) is proposed to solve reacting flow problems. This algorithm is based on a dimensionality reduction using Proper Orth…
Local manifold learning and its link to domain-based physics knowledge
Kamila Zdybał, Giuseppe D'Alessio, Antonio Attili +3
In many reacting flow systems, the thermo-chemical state-space is known or assumed to evolve close to a low-dimensional manifold (LDM). Various approaches are available to obtain t…