Neural Symbollic Regression Using Deep Learning and Sparse Modelling
A scalable and understandable neural-symbolic framework that treats neural networks as functional preconditioners for symbolic discovery, creating a solid link between neural approximation and the discovery of sparse equations for scientific machine learning.
U. Ravikumar, S. Sumitra
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