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Umberto Picchini

2 accepted papers

2023

Jana: Jointly amortized neural approximation of complex Bayesian models

UAI 2023poster

This work proposes “jointly amortized neural approximation” (JANA) of intractable likelihood functions and posterior densities arising in Bayesian surrogate modeling and simulation-based inference. We train three complementary networks in an end-to-end fashion: 1) a summary network to compress indiv…

Cited by 43SourcePDFScholar
2019

Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation

ICML 2019oral

We present a novel family of deep neural architectures, named partially exchangeable networks (PENs) that leverage probabilistic symmetries. By design, PENs are invariant to block-switch transformations, which characterize the partial exchangeability properties of conditionally Markovian processes.…