While conventional methods typically employ convolutional models to differentiate source and path effects, our approach relies on Symmetric Autoencoding (SymAE). SymAE enables us to examine the spatial patterns in earthquake data and effectively separate slow-scale source effects from fast-scale path effects. This separation helps us to determine earthquake source time functions more accurately, without being influenced by path effects.

On extracting coherent seismic wavefield using variational symmetric autoencoders
https://arxiv.org/abs/2411.15613
​​​​​​​Learning earthquake sources using symmetric autoencoders
https://arxiv.org/abs/2304.02404