Tempering chains achieve polynomial spectral gap lower bounds of order 11-12 for multimodal Gibbs measures without explicit energy landscape structure.
Exponential Convergence of Langevin Distributions and Their Discrete Approximations
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
verdicts
UNVERDICTED 3representative citing papers
Langevin sampling on the modern Hopfield energy produces training-free stochastic attention that transitions from exact retrieval to generation as temperature rises, with an entropy inflection condition marking the shift.
Brownian bridge importance sampling removes bias in maximum-likelihood estimation of Langevin diffusion parameters for autocorrelated, irregularly sampled animal telemetry data.
citing papers explorer
-
Rapid convergence of tempering chains to multimodal Gibbs measures
Tempering chains achieve polynomial spectral gap lower bounds of order 11-12 for multimodal Gibbs measures without explicit energy landscape structure.
-
Stochastic Attention via Langevin Dynamics on the Modern Hopfield Energy
Langevin sampling on the modern Hopfield energy produces training-free stochastic attention that transitions from exact retrieval to generation as temperature rises, with an entropy inflection condition marking the shift.
-
Unbiased likelihood estimation of the Langevin diffusion for animal movement modelling
Brownian bridge importance sampling removes bias in maximum-likelihood estimation of Langevin diffusion parameters for autocorrelated, irregularly sampled animal telemetry data.