We leverage variational autoencoders to generate transient light curves of distant exoplanets and stars in order to demonstrate the efficacy of deep learning techniques for this class of data. The ability to generate accurate light curves with desirable characteristics becomes more and more necessary with the success of recent astronomical missions and upcoming missions and will be a key enabler of the development of future models and research. The first study of its type to date, our initial results indicate a promising new research direction worthy of further development.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Generating Transit Light Curves with Variational Autoencoders


    Beteiligte:


    Erscheinungsdatum :

    01.07.2019


    Format / Umfang :

    1059968 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Variational Autoencoders

    Ghojogh, Benyamin / Crowley, Mark / Karray, Fakhri et al. | Springer Verlag | 2022


    Deep Tracking Portfolios Using Autoencoders and Variational Autoencoders

    Urrego, Daniel Aragón / Nieto, Oscar Eduardo Reyes / Quimbayo, Carlos Andrés Zapata | Springer Verlag | 2024


    Certifiably Robust Variational Autoencoders

    Barrett, Ben / Camuto, Alexander / Willetts, Matthew et al. | ArXiv | 2021

    Freier Zugriff

    Mixed-curvature Variational Autoencoders

    Skopek, Ondrej / Ganea, Octavian-Eugen / Bécigneul, Gary | ArXiv | 2019

    Freier Zugriff

    Diffusion Priors In Variational Autoencoders

    Wehenkel, Antoine / Louppe, Gilles | ArXiv | 2021

    Freier Zugriff