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Found 4 papers, 4 papers with code
Multi-View Symbolic Regression
We demonstrate the effectiveness of MvSR using data generated from known expressions, as well as real-world data from astronomy, chemistry and economy, for which an a priori analytical expression is not available.
Understanding of the properties of neural network approaches for transient light curve approximations
Modern-day time-domain photometric surveys collect a lot of observations of various astronomical objects and the coming era of large-scale surveys will provide even more information on their properties.
Supernova Light Curves Approximation based on Neural Network Models
Normalizing Flows exceeds Gaussian processes in terms of approximation quality as well.
Photometric Data-driven Classification of Type Ia Supernovae in the Open Supernova Catalog
We propose a novel approach for a machine-learning-based detection of the type Ia supernovae using photometric information.
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