Solar flare prediction with temporal convolutional networks

Abstract

Sequences are typically modelled with recurrent architectures, but growing research is finding convolutional architectures to also work well for sequence modelling [1]. We explore the performance of Temporal Convolutional Networks (TCNs) when applied to an important sequence modelling task: solar flare prediction. We take this approach, as our future goal is to apply techniques developed for probing and interpreting general convolutional neural networks (CNNs) to solar flare prediction.