Jeffreys Flow distills Parallel Tempering trajectories via Jeffreys divergence to produce robust Boltzmann generators that suppress mode collapse and correct sampling inaccuracies for rare event sampling.
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Time delay likelihoods modeled with Gaussian processes develop a boundary-driven W-shape with a global maximum at the true delay and rises at observation window edges, misleading nested sampling and biasing H0 high.
In 1D all-bands-flat condensates, infinitesimal interactions trigger a geometry-driven transition to a nematic manifold for θ ≥ π/8, with density-modulated states at θ=π/4 thermally selected via order-by-disorder.
citing papers explorer
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Jeffreys Flow: Robust Boltzmann Generators for Rare Event Sampling via Parallel Tempering Distillation
Jeffreys Flow distills Parallel Tempering trajectories via Jeffreys divergence to produce robust Boltzmann generators that suppress mode collapse and correct sampling inaccuracies for rare event sampling.
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Global structure of the time delay likelihood
Time delay likelihoods modeled with Gaussian processes develop a boundary-driven W-shape with a global maximum at the true delay and rises at observation window edges, misleading nested sampling and biasing H0 high.
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Nematic Phase Transitions and Density Modulations in 1D Flat Band Condensates
In 1D all-bands-flat condensates, infinitesimal interactions trigger a geometry-driven transition to a nematic manifold for θ ≥ π/8, with density-modulated states at θ=π/4 thermally selected via order-by-disorder.