Derives non-asymptotic error bounds for standard, defensive, and self-normalized importance sampling with random KDE proposals from geometrically ergodic Markov chains, separating n^{-1/2} Monte Carlo error from MIAE/MISE proposal error.
and Kass, Robert E
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Slice Monte Carlo integration partitions parameter space with a surrogate to enable variance-reduced stratified Monte Carlo estimation of integrals involving expensive target functions.
A plug-and-play differentiable model bridging ray and wave optics for hybrid systems that enables end-to-end optimization of planar and conformal diffractive elements.
FIREFLY accelerates multi-mode GW ringdown analysis by analytically marginalizing QNM amplitudes and phases via Bayesian principles and importance sampling.
citing papers explorer
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Error Bounds for Importance Sampling with Estimated Proposal Distributions
Derives non-asymptotic error bounds for standard, defensive, and self-normalized importance sampling with random KDE proposals from geometrically ergodic Markov chains, separating n^{-1/2} Monte Carlo error from MIAE/MISE proposal error.
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Slice Monte Carlo Integration
Slice Monte Carlo integration partitions parameter space with a surrogate to enable variance-reduced stratified Monte Carlo estimation of integrals involving expensive target functions.
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A General Differentiable Ray-Wave Framework for Hybrid Refractive-Diffractive System Modeling and Optimization
A plug-and-play differentiable model bridging ray and wave optics for hybrid systems that enables end-to-end optimization of planar and conformal diffractive elements.
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A practical Bayesian method for gravitational-wave ringdown analysis with multiple modes
FIREFLY accelerates multi-mode GW ringdown analysis by analytically marginalizing QNM amplitudes and phases via Bayesian principles and importance sampling.