A quadratic classifier logit built from learned state embeddings converts forward-versus-reversed trajectory discrimination into a scalable entropy-production estimate plus a low-dimensional map of irreversible flow.
Here, α and β are the linear and nonlinear dispersions of the medium respectively
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Identifying nonequilibrium degrees of freedom in high-dimensional stochastic systems
A quadratic classifier logit built from learned state embeddings converts forward-versus-reversed trajectory discrimination into a scalable entropy-production estimate plus a low-dimensional map of irreversible flow.