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UID:20251119T234142EST-72476tcUO9@132.216.98.100
DTSTAMP:20251120T044142Z
DESCRIPTION:Title: Challenges in Bayesian Computing.\n\nAbstract: Computing
  is both the most mathematical and most applied aspect of statistics. We s
 hall talk about various urgent computing-related topics in statistical (in
  particular\, Bayesian) workflow\, including exploratory data analysis and
  model checking\, Hamiltonian Monte Carlo\, monitoring convergence of iter
 ative simulations\, scalable computing\, evaluation of approximate algorit
 hms\, predictive model evaluation\, and simulation-based calibration. This
  work is inspired by applications including survey research\, drug develop
 ment\, and environmental decision making.\n
DTSTART:20190322T193000Z
DTEND:20190322T203000Z
LOCATION:Room 1104\, Burnside Hall\, CA\, QC\, Montreal\, H3A 0B9\, 805 rue
  Sherbrooke Ouest
SUMMARY:Andrew Gelman\, Columbia University
URL:/mathstat/channels/event/andrew-gelman-columbia-un
 iversity-295584
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