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20132026
most citedIntegration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery

216 citations · 379 across the 13 of their papers we have counts for

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physics.comp-ph2022★ 26 cited

Discovering Conservation Laws using Optimal Transport and Manifold Learning

Peter Y. Lu, Rumen Dangovski, Marin Soljačić

Conservation laws are key theoretical and practical tools for understanding, characterizing, and modeling nonlinear dynamical systems. However, for many complex systems, the corres…

physics.comp-ph2019★ 35 cited

Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning

Peter Y. Lu, Samuel Kim, Marin Soljačić

Experimental data is often affected by uncontrolled variables that make analysis and interpretation difficult. For spatiotemporal systems, this problem is further exacerbated by th…