Principled Priors for Gaussian Processes

Michael Betancourt: Principled Priors for Gaussian Processes

Abstract: Gaussian processes are multifaceted creatures — despite being burdened with sophisticated mathematical originals they enjoy practical implementations that seem far too straightforward for their theoretical prestige. In this talk I will introduce the basics of Gaussian processes and their implementations before discussing how pathologies can quickly arise, significantly limiting their practical utility, if those mathematics are taken for granted. In particular I will discuss the potential benefit of full Bayesian inference with Gaussian processes and the careful prior models necessary to realize that potential.

Bio: Michael Betancourt is the principal research scientist with Symplectomorphic, LLC where he develops theoretical and methodological tools to support practical Bayesian inference. He is also a core developer of Stan, where he implements and tests these tools. In addition to hosting tutorials and workshops on Bayesian inference with Stan he also collaborates on analyses in epidemiology, pharmacology, and physics, amongst others. Before moving into statistics, Michael earned a B.S. from the California Institute of Technology and a Ph.D. from the Massachusetts Institute of Technology, both in physics.

Website: https://betanalpha.github.io
Twitter: @betanalpha

Agenda

6:30 - 7:00pm: Arrival & welcome to Lockton Re
7:00 pm: Presentation by Michael Betancourt