Adversarial Autoencoders in Operator Learning

• URL: http://arxiv.org/abs/2412.07811v1
• Date: Tue, 10 Dec 2024 03:54:55 GMT
• Title: Adversarial Autoencoders in Operator Learning
• Authors: Dustin Enyeart, Guang Lin,
• Abstract summary: Two prevalent neural operator architectures are DeepONets and Koopman autoencoders. An adversarial addition to an autoencoder have improved performance of autoencoders in various areas of machine learning.
• Score: 6.03891813540831
• License:
• 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.

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