Unifilarisation of stochastic Mealy machines is an instance of coalgebraic determinisation over monads with support structure, producing causal stochastic behaviours rather than Moore-style output distributions.
hub
Springer Monographs in Mathematics
3 Pith papers cite this work, alongside 2,478 external citations. Polarity classification is still indexing.
3
Pith papers citing it
2,478
external citations · OpenAlex
hub tools
years
2026 3representative citing papers
Positive Lyapunov exponents can block natural-innovation synchronization (hence usable functional dependence) for uniformly ergodic AR maps, even though Doeblin splitting always yields a geometric Bernoulli representation on an enlarged space.
Residual network Jacobians under Frobenius normalization have singular spectra that form trace-normalized Cartan orbits satisfying slack-aware margin inequalities bounding exponent drift to order (log M)/L in zero-slack cases.
citing papers explorer
-
Bayesian updates from coalgebraic determinisation
Unifilarisation of stochastic Mealy machines is an instance of coalgebraic determinisation over monads with support structure, producing causal stochastic behaviours rather than Moore-style output distributions.
-
Functional dependence and synchronous coupling in ergodic autoregressions
Positive Lyapunov exponents can block natural-innovation synchronization (hence usable functional dependence) for uniformly ergodic AR maps, even though Doeblin splitting always yields a geometric Bernoulli representation on an enlarged space.
-
Geometric and Spectral Alignment for Deep Neural Network I
Residual network Jacobians under Frobenius normalization have singular spectra that form trace-normalized Cartan orbits satisfying slack-aware margin inequalities bounding exponent drift to order (log M)/L in zero-slack cases.