arXiv stat.ML
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Reinforced sequential Monte Carlo for amortised sampling
arXiv:2510.11711v3 Announce Type: replace-cross Abstract: This paper proposes a synergy of amortised and particle-based methods for sampling from distributions defined by unnormalised density functions. We state a connection between sequential Monte Carlo (SMC) and neural sequential samplers trained by maximum-entropy