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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Generating Transit Light Curves with Variational Autoencoders


    Contributors:


    Publication date :

    2019-07-01


    Size :

    1059968 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    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

    Free access

    Mixed-curvature Variational Autoencoders

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

    Free access