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Learning interpretable dynamics of stochastic complex systems from experimental data

Biology

Learning interpretable dynamics of stochastic complex systems from experimental data

T. Gao, B. Barzel, et al.

Discover how the Langevin Graph Network Approach (LaGNA) revolutionizes the inference of stochastic differential equations from empirical data for complex networks. Developed by Ting-Ting Gao, Baruch Barzel, and Gang Yan, this innovative method outshines existing techniques, providing critical insights into bird flock dynamics and tau pathology in mice.

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