Using Neural Implicit Flow To Represent Latent Dynamics Of Canonical
Systems
Using Neural Implicit Flow To Represent Latent Dynamics Of Canonical
Systems
The recently introduced class of architectures known as Neural Operators has emerged as highly versatile tools applicable to a wide range of tasks in the field of Scientific Machine Learning (SciML), including data representation and forecasting. In this study, we investigate the capabilities of Neural Implicit Flow (NIF), a recently …