BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//UM//UM*Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:America/Detroit
TZURL:http://tzurl.org/zoneinfo/America/Detroit
X-LIC-LOCATION:America/Detroit
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20070311T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20071104T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260916T102711
DTSTART;TZID=America/Detroit:20261030T100000
DTEND;TZID=America/Detroit:20261030T110000
SUMMARY:Social / Informal Gathering:La Tertulia: Spanish Coffee Hour
DESCRIPTION:Hola! ¿Cómo estás?\n\n-Practice your Spanish-speaking skills with peers & instructors in a relaxed environment. All language levels and students are welcome to join the conversation.\n\n-Come & go as you please\; stay as little or as long as you would like!\n\n-Free coffee\, tea\, light snacks\, & baked goods.
UID:150691-21909924@events.umich.edu
URL:https://events.umich.edu/event/150691
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Coffee,Undergraduate Students,Undergraduate,Study Abroad,Spanish,Spain,Social,Romance Languages And Literatures,Networking,Latin America,Language,International,Games,Free,Food,European,Europe,Engaged Learning,Culture,Community Engagement,Community,Central America
LOCATION:Modern Languages Building - 4314 MLB
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20261021T091427
DTSTART;TZID=America/Detroit:20261030T100000
DTEND;TZID=America/Detroit:20261030T110000
SUMMARY:Workshop / Seminar:Neural simulation-based inference for scalable\, high-fidelity spatial modeling
DESCRIPTION:Neural simulation-based inference is a recent paradigm shift in statistical science that uses simulations from a statistical model to train a neural network for statistical inference. These neural models serve as fast and accurate amortized surrogates for classical inferential quantities\, such as point estimators\, confidence sets\, likelihoods\, posteriors or conditional distributions\, whose evaluation tends to be computationally intensive or wholly intractable for many complex statistical models. As such\, this approach holds the potential for massive scale-up and increased fidelity of statistical inference in complex real-world settings which have previously relied on crude approximations or overly simplified modeling. In this talk\, I will first give an overview of some of the key ideas in neural simulation-based inference. I will then describe our work on neural likelihood inference motivated by complex inferential problems in spatial and spatio-temporal statistics. Specific topics covered include scalable Gaussian process modeling of Earth science observations and circumventing intractable likelihoods in spatial extremes models and spatial transport error models\, with an application to constraining aerosol climate parameters.\n\n*Department reception in 450 West Hall after the seminar at 11:00 AM*
UID:153810-21916381@events.umich.edu
URL:https://events.umich.edu/event/153810
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Aem Featured,seminar,statistics,Talk
LOCATION:West Hall - 340
CONTACT:
END:VEVENT
END:VCALENDAR