In this talk we will provide a brief introduction to Sequential Monte Carlo (SMC) methods and provide a guide to diagnose posterior samples computed using SMC.
Pedro German Ramirez
In the year 2014 I completed my Bs. in Molecular Biology at the National University of San Luis, Argentina and in 2020 I finished my PhD in the Instute of Applied Mathematics (IMASL) while working within the Structural Bioinformatics Group (BIOS). My PhD thesis was centered around the use of a statiscal mechanics model to simulate biologically relevant systems of peptide-lipid interactions. Currently I’m doing my postdoc alongside Dr. Osvaldo Martin on probabilistic modeling and Sequential Monte Carlo.
Osvaldo is a researcher at the National Scientific and Technical Research Council in Argentina and is notably the author of the book Bayesian Analysis with Python, whose second edition was published in December 2018. He also teaches bioinformatics, data science and Bayesian data analysis, and is a core developer of PyMC3 and ArviZ, and recently started contributing to Bambi. Originally a biologist and physicist, Osvaldo trained himself to python and Bayesian methods – and what he’s doing with it is pretty amazing!
This is a PyMCon 2020 talk
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