antonio vergari
City of Edinburgh, Scotland, United Kingdom
Summary
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SeniorAntonio Vergari is a Reader (Associate Professor) of machine learning at the University of Edinburgh, with 15 years of research and teaching experience focused on deep learning and tractable probabilistic models. His work blends theoretical rigor with practical scalable inference and neural methods, contributing to both foundational ML and applied AI challenges. He has held roles at UCLA, MPI-IS, and Bari, progressing from PhD student to senior academic, and currently leads advanced ML research in the School of Informatics. He collaborates with international communities such as UCLA StarAI, probabilistic learning, and Empirical Inference, reflecting an active and broad research footprint. Based in Edinburgh, he balances research leadership with mentorship and teaching across the ML program. A nod to his motto “selfie non multiplicanda praeter necessitatem,” his approach emphasizes simplicity and elegance in modeling.
15 years of coding experience
Github Skills (117)
probabilistic-programming10
encoding10
mixture-model10
sampling10
autoencoder10
sum10
probability10
graphs10
distributions10
binding10
information-theory10
bayesian10
probabilistic-models10
sum-product10
probabilistic10
Programming languages (7)
Github contributions (5)
arranger1044/probabilistic-circuits
Apr 2020 - May 2022
A curated collection of papers on probabilistic circuits, computational graphs encoding tractable probability distributions.
Contributions:1 review, 54 commits, 15 PRs in 2 years 1 month
distributionscircuitsprobability-distributionsmachine-learningencoding
arranger1044/iSoul
Oct 2010 - May 2012
Contributions:56 commits, 4 comments in 1 year 7 months
mac-ossoulseekmacos-xmacos
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