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An Introduction to Bayesian inference by Peter Green (2011)


Peter Green’s introductory lecture on Bayesian inference can be found here: http://videolectures.net/mlss2011_green_bayesian/. Description: Inference is the process of discovering from data about mechanisms that may have caused or generated that data, or at least explain it. The goals are varied – perhaps simply predicting future data, or more ambitiously drawing conclusions about scientific or societal […]

January 20, 2021


Video, Slides, and Code: Nonparametric Bayes (by Tamara Broderick)


Tamara Broderick has a wonderful information set (Video, Slides, Code) about Nonparametric Bayes. Check it out here: http://people.csail.mit.edu/tbroderick/tutorial_2016_mlss_cadiz.html!


Video and Slides: Variational Bayes and Beyond (by Tamara Broderick)


The ICML 2018 tutorial by Tamara Broderick entitled “Variational Bayes and beyond: Bayesian inference for big data” can be found here: http://people.csail.mit.edu/tbroderick/tutorial_2018_icml.html. Abstract: Bayesian methods exhibit a number of desirable properties for modern data analysis—including (1) coherent quantification of uncertainty, (2) a modular modeling framework able to capture complex phenomena, (3) the ability to incorporate […]


“It Pays to Go Bayes”, a video lectures series on Bayesian Methods in Econometrics and Forecasting


“It Pays to Go Bayes” [Youtube link] is a video lecture series on Bayesian Methods in Econometrics and Forecasting edited by K. Surekha Rao. This series contains twenty-four foundational lectures by prominent Bayesians Arnold Zellner, Jayanta Kumar Gosh, Prem Goel, Wolfgang Wolfgang Polasek, William Griffiths, and a few early Indian Bayesians. An international workshop on […]

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January 5, 2021


ISBA-BioPharma Webinar: Bayesian influenza forecasting modelling


The ISBA Biostatistics and Pharmaceutical Statistics Section (https://isba-biostatspharma.github.io/) is pleased to announce our very first webinar. David Osthus will talk about “Bayesian influenza forecasting modelling,” with a focus on recent work on the multiscale influenza forecasting model DANTE, a collaboration with Kelly R Moran. The preprint is available here: https://nature-research-under-consideration.nature.com/users/37265-nature-communications/posts/55426-multiscale-influenza-forecasting. This model extends Dr. Osthus […]

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March 18, 2020


BA Webinar: A Novel Algorithmic Approach to Bayesian Logic Regression


The Discussion Paper of the March 2020 issue of Bayesian Analysis: “A Novel Algorithmic Approach to Bayesian Logic Regression by Aliaksandr Hubin, Geir Storvik, and Florian Frommlet with the presence of the authors, and Katja Ickstadt, Malgorzata Bogdan, Blazej Miasejedow and Jonas Wallin Wednesday, February 26, 2020 5:00 pm CET The manuscript can be downloaded […]

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February 26, 2020


BA Webinar: Latent Nested Nonparametric Priors


The Discussion Paper of the December issue of Bayesian Analysis: “Latent Nested Nonparametric Priors” by Federico Camerlenghi, David B. Dunson, Antonio Lijoi, Igor Prünster, and Abel Rodríguez will be formally presented in a Webinar on Wednesday, November 27, 2019 – 5:00 pm CET with the presence of Federico Camerlenghi and other authors, and Mario Beraha […]

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November 27, 2019


BA Webinar: Bayesian Conjugate Gradient Method


Presentation of the Discussion Paper of the September 2019 issue of Bayesian Analysis Panelists: Jon Cockayne, Chris Oates (authors) and Ethan Fang (Discussant) A Bayesian Conjugate Gradient Method Manuscript (with Discussion) https://projecteuclid.org/euclid.ba/1558144846

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October 2, 2019


ISBA 2018 Bayesian Foundations Lecture by Judith Rousseau


Asymptotic behaviour of credible regions Judith Rousseau The reknown theorem of Bernstein von Mises in regular finite-dimensional models has numerous interesting consequences, in particular, it implies that a large class of credible regions are also asymptotically confidence regions, which in turns imply that different priors lead to the same credible regions to first order. Unfortunately, […]

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June 28, 2018


ISBA 2018 Bayesian Foundations Lecture by Ed George


Bayesian Hospital Mortality Rate Estimation: Calibration and Standardization for Public Reporting Edward I. George Bayesian models are increasingly fit to large administrative data sets and then used to make individualized recommendations. In particular, Medicare’s Hospital Compare webpage provides information to patients about specific hospital mortality rates for a heart attack or Acute Myocardial Infarction (AMI). […]

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