<ul><li>Modeling stochastic differential equations (SDEs) is crucial for understanding complex dynamical systems in various scientific fields.</li><li>The Finite Expression Method (FEX) is introduced as a symbolic learning approach to derive interpretable mathematical representations of the deterministic component of SDEs.</li><li>FEX integrates with generative modeling techniques to provide a comprehensive representation of SDEs, improving long-term predictions and generalization beyond training domain.</li><li>FEX not only enhances prediction accuracy but also offers valuable scientific insights into the underlying dynamics of the systems, opening new possibilities for new discoveries.</li></ul>

Identifying Unknown Stochastic Dynamics via Finite expression methods

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