A neural pipeline discovers projectable Lie-point symmetries of SDEs from trajectory data and recovers the known symmetry algebras of four benchmark SDEs.
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LieStoNet: Learning Lie Symmetries from Spatiotemporal Data for Stochastic Dynamical Systems
A neural pipeline discovers projectable Lie-point symmetries of SDEs from trajectory data and recovers the known symmetry algebras of four benchmark SDEs.