Laplace's Demon: Bayesian Machine Learning at Scale has a few announcements.
Firstly registration is now open for Jake Hofman 17 June talk: "How visualizing inferential uncertainty can mislead readers about treatment effects in scientific results". Jake is a Senior Principal Researcher at Microsoft Research, New York. We very much look forward to his insights on visualizing uncertainty. It is at 15.00 UTC, to see it in your local time zone please go to the registration page. The talk is on this Wednesday. Please register at: https://ailab.criteo.com/laplaces-demon-bayesian-machine-learning-at-scale/ Secondly Christian Robert's talk on approximate Bayesian computation is now online. Christian not only presents state of results showing ABC using Gibbs like steps, but also takes time to give the basis of ABC methods and takes many questions. https://www.youtube.com/watch?v=Aq4juvSsz9Y Finally we have a new website, giving details of upcoming talks including A/Prof Aki Vehatari's 24 June on "Use of reference models in variable selection". https://ailab.criteo.com/laplaces-demon-bayesian-machine-learning-at-scale/ Also upcoming: 17 Jun, Jake Hofman, "How visualizing inferential uncertainty can mislead readers about treatment effects in scientific results" 24 Jun, Aki Vehtari, "Use of reference models in variable selection" 1 Jul John Ormerod 8 Jul Victor Elvira 29 Jul Cheng Zhang 26 Aug Andrew Gelman Looking forward to seeing you soon, The Laplace's Demon Team
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