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.
Simulation and Training Hyperparameters of the N = 16 Bead System for Directly-Learned Lin- ear Projections Hyperparameter values correspond to those used for data plotted in Fig
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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.