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  • 2024

    Optimization of Tollmien-Schlichting waves control: comparison between a deep reinforcement learning and particle swarm optimization approach

    Mohammadikalakoo, B., Kotsonis, M. & Doan, N. A. K., 2024, Proceedings of the AIAA SCITECH 2024 Forum. American Institute of Aeronautics and Astronautics Inc. (AIAA), 14 p. AIAA 2024-0930

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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  • Towards Universal Parameterization: Using Variational Autoencoders to Parameterize Airfoils

    Swannet, K., Varriale, C. & Doan, N. A. K., 2024, Proceedings of the AIAA SCITECH 2024 Forum. American Institute of Aeronautics and Astronautics Inc. (AIAA), 16 p. AIAA 2024-0686

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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  • 2023

    Clustering-Based Identification of Precursors of Extreme Events in Chaotic Systems

    Gołyska, U. & Doan, N. A. K., 2023, Lecture Notes in Computer Science - ICCS2023: Computational Science – ICCS 2023 23rd International Conference, Prague, Czech Republic, July 3–5, 2023, Proceedings, Part IV. Kozyrev, D. V. (ed.). Springer, Vol. 10476. p. 317-327 (Lecture Notes in Computer Science - ICCS2023; vol. 10476).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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  • Convolutional Autoencoder for the Spatiotemporal Latent Representation of Turbulence

    Doan, N. A. K., Racca, A. & Magri, L., 2023, Lecture Notes in Computer Science - ICCS 2023: Computational Science – ICCS 2023 23rd International Conference, Prague, Czech Republic, July 3–5, 2023, Proceedings, Part IV. Kozyrev, D. V. (ed.). Springer, Vol. 10476. p. 328-335 (Lecture Notes in Computer Science - ICCS2023; vol. 10476).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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    13 Downloads (Pure)
  • 2021

    Auto-Encoded Reservoir Computing for Turbulence Learning

    Doan, N. A. K., Polifke, W. & Magri, L., 2021, Computational Science – ICCS 2021 - 21st International Conference, Proceedings. Paszynski, M., Kranzlmüller, D., Kranzlmüller, D., Krzhizhanovskaya, V. V., Dongarra, J. J., Sloot, P. M., Sloot, P. M. & Sloot, P. M. (eds.). Springer, p. 344-351 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12746 LNCS).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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    3 Citations (Scopus)
    53 Downloads (Pure)
  • 2020

    Learning hidden states in a chaotic system: A physics-informed echo state network approach

    Doan, N. A. K., Polifke, W. & Magri, L., 2020, Computational Science – ICCS 2020 - 20th International Conference, Proceedings. Krzhizhanovskaya, V. V., Závodszky, G., Lees, M. H., Sloot, P. M. A., Sloot, P. M. A., Sloot, P. M. A., Dongarra, J. J., Brissos, S. & Teixeira, J. (eds.). Springer, p. 117-123 7 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12142 LNCS).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

    Open Access
    3 Citations (Scopus)
  • 2019

    Physics-Informed Echo State Networks for Chaotic Systems Forecasting

    Doan, N. A. K., Polifke, W. & Magri, L., 2019, Computational Science – ICCS 2019 - 19th International Conference, Proceedings. Rodrigues, J. M. F., Cardoso, P. J. S., Monteiro, J., Lam, R., Krzhizhanovskaya, V. V., Lees, M. H., Sloot, P. M. A. & Dongarra, J. J. (eds.). Springer, p. 192-198 7 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11539 LNCS).

    Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

    20 Citations (Scopus)