BEGIN:VCALENDAR
VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20261023T003840Z
UID:https://www.mpgc-mainz.de/events/30803/2368
DTSTART;VALUE=DATE:20220518
DTEND;VALUE=DATE:20220519
CLASS:PUBLIC
CREATED:20220408T082739Z
DESCRIPTION:Atmospheric field experiments create unique datasets and cannot
  be repeated to increase data coverage or precision. However\, many observ
 ables are closely connected through chemical reactions. Can this dependenc
 e be used to decrease uncertainty of poorly measured variables with the he
 lp of high precision measurements? Yes – the sequential monte carlo filt
 er combines prior knowledge of a variable through system dynamics with act
 ual measurements in a Bayesian way.\nSpeaker: Lenard Röder
LAST-MODIFIED:20220516T123800Z
LOCATION:
SUMMARY:Lenard Röder: Sequential Monte Carlo Filters for Atmospheric Field
  Experiments
URL;VALUE=URI:https://www.mpgc-mainz.de/events/30803/2368
END:VEVENT
END:VCALENDAR