Data-driven Lie point symmetry detection for continuous dynamical systems
Alex Gabel,
Rick Quax,
Efstratios Gavves
Abstract:Symmetry detection, the task of discovering the underlying symmetries of a given dataset, has been gaining popularity in the machine learning community, particularly in science and engineering applications. Most previous works focus on detecting "canonical" symmetries such as translation, scaling, and rotation, and cast the task as a modeling problem involving complex inductive biases and architecture design of neural networks. We challenge these assumptions and propose that instead of constructing biases, we … Show more
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