Log d observation time is sufficient and necessary to exactly recover the latent network for sparse weak-interaction stationary Hawkes processes.
Elsevier, 2014
4 Pith papers cite this work. Polarity classification is still indexing.
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Langevin dynamics on spiked Wigner matrices achieve O(log N) mixing from symmetric initializations even below the critical temperature, while worst-case mixing times are exponential with rate equal to the free-energy difference between spiked and null models.
A new one-parameter linear benchmark SDE is derived and used to demonstrate that lower-order explicit stochastic integrators can outperform higher-order ones in stability and accuracy over ranges of time-step sizes.
Existence and uniqueness of variational solutions are proved for a coupled SPDE-ODE system modeling stochastically perturbed cell electropermeabilization with degenerate multiplicative noise.
citing papers explorer
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On Observation Time for Recovering Latent Hawkes Networks
Log d observation time is sufficient and necessary to exactly recover the latent network for sparse weak-interaction stationary Hawkes processes.
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Mixing times of Langevin dynamics for spiked matrix models
Langevin dynamics on spiked Wigner matrices achieve O(log N) mixing from symmetric initializations even below the critical temperature, while worst-case mixing times are exponential with rate equal to the free-energy difference between spiked and null models.
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Numerical stability revisited: A family of benchmark problems for the analysis of explicit stochastic differential equation integrators
A new one-parameter linear benchmark SDE is derived and used to demonstrate that lower-order explicit stochastic integrators can outperform higher-order ones in stability and accuracy over ranges of time-step sizes.
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Stochastically perturbed model of cell electropermeabilization
Existence and uniqueness of variational solutions are proved for a coupled SPDE-ODE system modeling stochastically perturbed cell electropermeabilization with degenerate multiplicative noise.