V. Tagarielli

Encoding multiphase dynamics to predict spatiotemporal evolution via latent-space operators

This work proposes a two-stage decoupled training paradigm that independently optimizes a Kolmogorov–Arnold autoencoder for spatial reduced-order representation and a latent-space operator network for initial-to-future dynamics, and proposes reduced-order and fusion schemes for multiphase problems to characterize the a...