Generalized One-Shot Transfer Learning of Linear Ordinary and Partial Differential Equations

This work describes a process to train PINNs on equations with varying conditions across multiple “heads" and shows how this multi-headed training process can be used to yield a latent space representation of a particular differential equation form.