I found his paper: https://iopscience.iop.org/article/10.3847/1538-3881/ad7fe6 (no paywall 😃)
From the intro:
VARnet leverages a one-dimensional wavelet decomposition in order to minimize the impact of spurious data on the analysis, and a novel modification to the discrete Fourier transform (DFT) to quickly detect periodicity and extract features of the time series. VARnet integrates these analyses into a type prediction for the source by leveraging machine learning, primarily CNN.
They start with some good old fashioned signal processing, before feeding the result into a neutral net. The NN was trained on synthetic data.
FC = Fully Connected layer, so they’re mixing FC with mostly convolutional layers in their NN. I haven’t read the whole paper, I’m happy to be corrected.
It uses a neutral net that he designed and trained, so it is AI. The public’s view of “AI” seems mostly the generation stuff like chatbots and image gen, but deep learning is perfect for science and medical fields.