BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Venue Radar//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:AISTATS 2027 Calendar
BEGIN:VEVENT
UID:aistats-2027-deadline-abstract@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART:20260930T115900Z
DTEND:20260930T125900Z
SUMMARY:[Learning Theory & Statistical Foundations][Machine Learning] AISTA
 TS 2027 - Abstract submission deadline
DESCRIPTION:Conference title: International Conference on Artificial Intell
 igence and Statistics\nWebsite: https://aistats.org/aistats2027/index.htm
 l\nSource URL: https://aistats.org/aistats2027/dates.html\nLocation: Mont
 real\, Quebec\, Canada\nTopics: Learning Theory & Statistical Foundations
 \, Machine Learning\, Probabilistic\, Causal & Uncertainty ML\, Time Seri
 es & Sequential Data\nSize: L\nSubmission type: Paper-based\nConfidence: 
 confirmed\nLast checked date: 2026-09-14\nNotes: Official AISTATS 2027 pa
 ges confirm Montreal\, May 3-6\, 2027\, and the Sep 29 abstract and Oct 6
  full-paper deadlines (AoE).\nScope: Research at the interface of artific
 ial intelligence\, machine learning\, and statistics. Its defining emphas
 is is on statistical foundations and methodology for learning and inferen
 ce\, rather than a particular application domain. Research bridges statis
 tical reasoning and learning algorithms\, with archival contributions to 
 both communities.\nAdditional topics: \nScope sources (2027): https://ais
 tats.org/aistats2027/\, https://aistats.org/aistats2027/call-for-papers.h
 tml\nScope last checked: 2026-10-07
URL:https://aistats.org/aistats2027/dates.html
END:VEVENT
BEGIN:VEVENT
UID:aistats-2027-deadline-full-paper@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART:20261007T115900Z
DTEND:20261007T125900Z
SUMMARY:[Learning Theory & Statistical Foundations][Machine Learning] AISTA
 TS 2027 - Full paper submission deadline
DESCRIPTION:Conference title: International Conference on Artificial Intell
 igence and Statistics\nWebsite: https://aistats.org/aistats2027/index.htm
 l\nSource URL: https://aistats.org/aistats2027/dates.html\nLocation: Mont
 real\, Quebec\, Canada\nTopics: Learning Theory & Statistical Foundations
 \, Machine Learning\, Probabilistic\, Causal & Uncertainty ML\, Time Seri
 es & Sequential Data\nSize: L\nSubmission type: Paper-based\nConfidence: 
 confirmed\nLast checked date: 2026-09-14\nNotes: Official AISTATS 2027 pa
 ges confirm Montreal\, May 3-6\, 2027\, and the Sep 29 abstract and Oct 6
  full-paper deadlines (AoE).\nScope: Research at the interface of artific
 ial intelligence\, machine learning\, and statistics. Its defining emphas
 is is on statistical foundations and methodology for learning and inferen
 ce\, rather than a particular application domain. Research bridges statis
 tical reasoning and learning algorithms\, with archival contributions to 
 both communities.\nAdditional topics: \nScope sources (2027): https://ais
 tats.org/aistats2027/\, https://aistats.org/aistats2027/call-for-papers.h
 tml\nScope last checked: 2026-10-07
URL:https://aistats.org/aistats2027/dates.html
END:VEVENT
BEGIN:VEVENT
UID:aistats-2027-conference@scientific-conference-calendar
DTSTAMP:19700101T000000Z
DTSTART;VALUE=DATE:20270503
DTEND;VALUE=DATE:20270507
SUMMARY:[Learning Theory & Statistical Foundations][Machine Learning] AISTA
 TS 2027 - Conference
DESCRIPTION:Conference title: International Conference on Artificial Intell
 igence and Statistics\nWebsite: https://aistats.org/aistats2027/index.htm
 l\nSource URL: https://aistats.org/aistats2027/index.html\nLocation: Mont
 real\, Quebec\, Canada\nTopics: Learning Theory & Statistical Foundations
 \, Machine Learning\, Probabilistic\, Causal & Uncertainty ML\, Time Seri
 es & Sequential Data\nSize: L\nSubmission type: Paper-based\nConfidence: 
 confirmed\nLast checked date: 2026-09-14\nNotes: Official AISTATS 2027 pa
 ges confirm Montreal\, May 3-6\, 2027\, and the Sep 29 abstract and Oct 6
  full-paper deadlines (AoE).\nScope: Research at the interface of artific
 ial intelligence\, machine learning\, and statistics. Its defining emphas
 is is on statistical foundations and methodology for learning and inferen
 ce\, rather than a particular application domain. Research bridges statis
 tical reasoning and learning algorithms\, with archival contributions to 
 both communities.\nAdditional topics: \nScope sources (2027): https://ais
 tats.org/aistats2027/\, https://aistats.org/aistats2027/call-for-papers.h
 tml\nScope last checked: 2026-10-07
URL:https://aistats.org/aistats2027/index.html
LOCATION:Montreal\, Quebec\, Canada
END:VEVENT
END:VCALENDAR