| Manifold-informed state vector subset for reduced-order modeling K Zdybał, JC Sutherland, A Parente Proceedings of the Combustion Institute 39 (4), 5145--5154, 2022 | 27 | 2022 |
| PCAfold: Python software to generate, analyze and improve PCA-derived low-dimensional manifolds K Zdybał, E Armstrong, A Parente, JC Sutherland SoftwareX 12, 100630, 2020 | 24 | 2020 |
| Cost function for low-dimensional manifold topology assessment K Zdybał, E Armstrong, JC Sutherland, A Parente Scientific Reports 12 (1), 14496, 2022 | 19 | 2022 |
| Advancing Reacting Flow Simulations with Data-Driven Models K Zdybal, G D’Alessio, G Aversano, MR Malik, A Coussement, ... Data-Driven Fluid Mechanics: Combining First Principles and Machine Learning …, 2023 | 13 | 2023 |
| Reduced-order modeling of supersonic fuel–air mixing in a multi-strut injection scramjet engine using machine learning techniques AC Ispir, K Zdybał, BH Saracoglu, T Magin, A Parente, A Coussement Acta Astronautica 202, 564-584, 2023 | 11 | 2023 |
| Local manifold learning and its link to domain-based physics knowledge K Zdybał, G D’Alessio, A Attili, A Coussement, JC Sutherland, A Parente Applications in Energy and Combustion Science 14, 100131, 2023 | 8 | 2023 |
| PCAfold 2.0—Novel tools and algorithms for low-dimensional manifold assessment and optimization K Zdybał, E Armstrong, A Parente, JC Sutherland SoftwareX 23, 101447, 2023 | 7 | 2023 |
| Reduced-Order Modeling of Reacting Flows Using Data-Driven Approaches K Zdybał, MR Malik, A Coussement, JC Sutherland, A Parente Machine Learning and Its Application to Reacting Flows: ML and Combustion …, 2023 | 4 | 2023 |
| Improving reduced-order models through nonlinear decoding of projection-dependent outputs K Zdybał, A Parente, JC Sutherland Patterns 4 (11), 2023 | 2 | 2023 |
| Reduced-order modeling of turbulent reacting flows using data-driven approaches K Zdybał Université libre de Bruxelles, 2023 | 1 | 2023 |
| On the effect of manifold topology in reduced-order modeling of turbulent combustion K Zdybał, JC Sutherland, A Parente | | 2023 |
| ON THE USE OF PROJECTION TO LATENT STRUCTURES AND GAUSSIAN PROCESS REGRESSION FOR CHEMISTRY REDUCTION H Dave, MR Malik, K Zdybal, HG Im, A Parente | | 2023 |
| Topological characteristics of low-dimensional manifolds in reduced-order modeling of turbulent combustion JC Sutherland, K Zdybal SIAM Conference on Computational Science and Engineering, Amsterdam, The …, 2023 | | 2023 |
| Reduced-order modeling with a regression-aware autoencoder K Zdybal, A Parente, JC Sutherland SIAM Conference on Computational Science and Engineering, Amsterdam, The …, 2023 | | 2023 |
| Reduced-order modeling of reacting flows with a regression-aware autoencoder K Zdybal, A Parente, JC Sutherland 13th US National Combustion Meeting, College Station, TX, USA, 2023 | | 2023 |
| The tensor necessity - a short story about momentum transport in fluids K Zdybał | | 2022 |
| Supplementary material for: Cost function for low-dimensional manifold topology assessment K Zdybał, E Armstrong, JC Sutherland, A Parente | | 2022 |
| Data-enhanced analysis, parameterisation and reduced-order modelling of turbulent reacting flows A Parente, L Donato, K Zdybał, A Procacci, M Savarese 18th International Conference on Numerical Combustion, La Jolla, USA, 2022 | | 2022 |
| Characterizing manifold topologies for reduced-order modeling K Zdybał, MR Malik, E Armstrong, JC Sutherland, A Parente 18th International Conference on Numerical Combustion, La Jolla, USA, 2022 | | 2022 |
| Cost function for assessing the quality of low-dimensional manifolds K Zdybał, E Armstrong, JC Sutherland, A Parente SIAM Conference on Mathematics of Data Science, San Diego, CA, USA, 2022 | | 2022 |
Alessandro ParenteUniversité Libre de Bruxelles在 ulb.ac.be 的电子邮件经过验证
