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Adversarial Autoencoders in Operator Learning

Machine Learning 2024-12-12 v1

Abstract

DeepONets and Koopman autoencoders are two prevalent neural operator architectures. These architectures are autoencoders. An adversarial addition to an autoencoder have improved performance of autoencoders in various areas of machine learning. In this paper, the use an adversarial addition for these two neural operator architectures is studied.

Cite

@article{arxiv.2412.07811,
  title  = {Adversarial Autoencoders in Operator Learning},
  author = {Dustin Enyeart and Guang Lin},
  journal= {arXiv preprint arXiv:2412.07811},
  year   = {2024}
}

Comments

arXiv admin note: substantial text overlap with arXiv:2412.06686, arXiv:2412.04578

R2 v1 2026-06-28T20:29:57.570Z