3 papers
cs.LG2026
Boosted GFlowNets: Improving Exploration via Sequential Learning
Pedro Dall'Antonia, Tiago da Silva, Daniel Augusto de Souza +2
Generative Flow Networks (GFlowNets) are powerful samplers for compositional objects that, by design, sample proportionally to a given non-negative reward. Nonetheless, in practice…
stat.ML2025
Infinite Neural Operators: Gaussian processes on functions
Daniel Augusto de Souza, Yuchen Zhu, Harry Jake Cunningham +3
A variety of infinitely wide neural architectures (e.g., dense NNs, CNNs, and transformers) induce Gaussian process (GP) priors over their outputs. These relationships provide both…
cs.LG2024
Streaming Bayes GFlowNets
Tiago da Silva, Daniel Augusto de Souza, Diego Mesquita
Bayes' rule naturally allows for inference refinement in a streaming fashion, without the need to recompute posteriors from scratch whenever new data arrives. In principle, Bayesia…