Author

Tiago da Silva

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Preprint Aug 2026

Path-dependent Discrete Amortized Inference

We consider the problem of sampling compositional and discrete objects from a given unnormalized posterior distribution. Notably, recent studies have shown that this problem can be efficiently solved by learning a deterministic Markov Decision Process (MDP) that progressively builds each object in proportion to the pos...

Tiago da Silva, Esmeralda S. Whitammer, S. Lahlou · 0 citations

#machine learning Preprint Sep 2026

Particle GFlowNets: Rethinking Generative Marginalization Models

This work describes an automatic criterion for full-state rejuvenation of the Gibbs sampler, derived from the Gelman-Rubin statistic, which plays a key role in speeding up learning convergence.

Tiago da Silva, Diego Mesquita, S. Lahlou · 0 citations