How to generate an object under an ordinary Boltzmann distribution via an exponential Boltzmann sampler
Olivier Bodini (LIP6)

TL;DR
This paper introduces a method to efficiently convert an exponential Boltzmann sampler into an ordinary Boltzmann sampler, facilitating easier generation of objects following the ordinary Boltzmann distribution.
Contribution
It provides a novel technique for deriving an ordinary Boltzmann sampler from an exponential one, improving sampling efficiency.
Findings
Efficient conversion method demonstrated
Reduces computational complexity in sampling
Applicable to various combinatorial objects
Abstract
This short note presents an efficient way to derive from an exponential Boltzmann sampler a ordinary Boltzmann sampler
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Taxonomy
TopicsMarkov Chains and Monte Carlo Methods · Generative Adversarial Networks and Image Synthesis · Diffusion and Search Dynamics
