Multivariate Modeling of Quasar Variability with an Attention-based Variational Autoencoder
Published in Durham e-Theses, 2024
This thesis investigated novel methods for modeling irregular & multivariate time series data of Active Galactic Nuclei (AGN), for the sake of improving both existing techniques for reverberation mapping and anomaly detection.
Recommended citation: M. Lowery, "Multivariate Modeling of Quasar Variability with an Attention-based Variational Autoencoder," Master’s thesis, Durham University, 2024.
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