MODNO: Multi Operator Learning With Distributed Neural Operators

arXiv:2404.02892v1 Announce Type: new
Abstract: The study of operator learning involves the utilization of neural networks to approximate operators. Traditionally, the focus has been on single-operator learning (SOL). However, recent advances have rapidly expanded this to include the approximation of multiple operators using foundation models equipped with millions or billions of trainable parameters, leading to the research of multi-operator learning (MOL). In this paper, we present a novel distributed training approach aimed at enabling a single neural operator with significantly …

abstract advances approximation arxiv cs.lg cs.na distributed focus foundation however math.na multiple networks neural networks operators study type