mlsanityData to 14 Oct 2026

Differential Informed Auto-Encoder

arXiv 2410.18593 ↗First posted 24 Oct 2024cs.LGcited by 0

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Abstract (arXiv)

In this article, an encoder was trained to obtain the inner structure of the original data by obtain a differential equations. A decoder was trained to resample the original data domain, to generate new data that obey the differential structure of the original data using the physics-informed neural network.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 2 references that are in the map. First posted on arXiv 24 Oct 2024.

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References · 1

  1. 2017Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equationscited by 373

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