Latent assimilation with implicit neural representations for unknown dynamics

arXiv:2309.09574v2 Announce Type: replace
Abstract: Data assimilation is crucial in a wide range of applications, but it often faces challenges such as high computational costs due to data dimensionality and incomplete understanding of underlying mechanisms. To address these challenges, this study presents a novel assimilation framework, termed Latent Assimilation with Implicit Neural Representations (LAINR). By introducing Spherical Implicit Neural Representations (SINR) along with a data-driven uncertainty estimator of the trained neural networks, LAINR enhances efficiency in assimilation process. Experimental results …

abstract applications arxiv challenges computational costs cs.lg data dimensionality dynamics framework implicit neural representations math.mp math.oc math-ph novel physics.ao-ph study type understanding