BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Venue Radar//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:UAI 2026 Calendar BEGIN:VEVENT UID:uai-2026-deadline-full-paper@scientific-conference-calendar DTSTAMP:19700101T000000Z DTSTART:20260226T115900Z DTEND:20260226T125900Z SUMMARY:[Probabilistic\, Causal & Uncertainty ML][Machine Learning] UAI 202 6 - Paper submission deadline DESCRIPTION:Conference title: Conference on Uncertainty in Artificial Intel ligence\nWebsite: https://www.auai.org/uai2026/\nSource URL: https://www. auai.org/uai2026/important_dates\nLocation: Amsterdam\, Netherlands\nTopi cs: Probabilistic\, Causal & Uncertainty ML\, Machine Learning\, Learning Theory & Statistical Foundations\nSize: L\nSubmission type: Paper-based\ nConfidence: confirmed\nLast checked date: 2026-08-20\nNotes: Official UA I 2026 pages list tutorials\, main conference\, workshops\, and paper sub mission deadline.\nScope: Learning and reasoning under uncertainty\, cent ered on probabilistic and Bayesian modeling\, graphical models\, causal i nference\, approximate inference\, and decision theory. Includes Monte Ca rlo and variational methods\, uncertainty quantification\, sequential mod els\, and principled analysis of learning algorithms. Uncertainty is the organizing theme\, not just another application of general-purpose AI.\nA dditional topics: Deep Representation Learning\, Reinforcement Learning\, Time Series & Sequential Data\, Explainability & Interpretability\, Robu stness & Safety\nScope sources (2026): https://www.auai.org/uai2026/subje ct_areas\, https://www.auai.org/uai2026/call_for_papers\nScope last check ed: 2026-10-07 URL:https://www.auai.org/uai2026/important_dates END:VEVENT BEGIN:VEVENT UID:uai-2026-deadline-camera-ready@scientific-conference-calendar DTSTAMP:19700101T000000Z DTSTART:20260709T115900Z DTEND:20260709T125900Z SUMMARY:[Probabilistic\, Causal & Uncertainty ML][Machine Learning] UAI 202 6 - Camera-ready deadline DESCRIPTION:Conference title: Conference on Uncertainty in Artificial Intel ligence\nWebsite: https://www.auai.org/uai2026/\nSource URL: https://www. auai.org/uai2026/important_dates\nLocation: Amsterdam\, Netherlands\nTopi cs: Probabilistic\, Causal & Uncertainty ML\, Machine Learning\, Learning Theory & Statistical Foundations\nSize: L\nSubmission type: Paper-based\ nConfidence: confirmed\nLast checked date: 2026-08-20\nNotes: Official UA I 2026 pages list tutorials\, main conference\, workshops\, and paper sub mission deadline.\nScope: Learning and reasoning under uncertainty\, cent ered on probabilistic and Bayesian modeling\, graphical models\, causal i nference\, approximate inference\, and decision theory. Includes Monte Ca rlo and variational methods\, uncertainty quantification\, sequential mod els\, and principled analysis of learning algorithms. Uncertainty is the organizing theme\, not just another application of general-purpose AI.\nA dditional topics: Deep Representation Learning\, Reinforcement Learning\, Time Series & Sequential Data\, Explainability & Interpretability\, Robu stness & Safety\nScope sources (2026): https://www.auai.org/uai2026/subje ct_areas\, https://www.auai.org/uai2026/call_for_papers\nScope last check ed: 2026-10-07 URL:https://www.auai.org/uai2026/important_dates END:VEVENT BEGIN:VEVENT UID:uai-2026-conference@scientific-conference-calendar DTSTAMP:19700101T000000Z DTSTART;VALUE=DATE:20260817 DTEND;VALUE=DATE:20260822 SUMMARY:[Probabilistic\, Causal & Uncertainty ML][Machine Learning] UAI 202 6 - Conference DESCRIPTION:Conference title: Conference on Uncertainty in Artificial Intel ligence\nWebsite: https://www.auai.org/uai2026/\nSource URL: https://www. auai.org/uai2026/\nLocation: Amsterdam\, Netherlands\nTopics: Probabilist ic\, Causal & Uncertainty ML\, Machine Learning\, Learning Theory & Stati stical Foundations\nSize: L\nSubmission type: Paper-based\nConfidence: co nfirmed\nLast checked date: 2026-08-20\nNotes: Official UAI 2026 pages li st tutorials\, main conference\, workshops\, and paper submission deadlin e.\nScope: Learning and reasoning under uncertainty\, centered on probabi listic and Bayesian modeling\, graphical models\, causal inference\, appr oximate inference\, and decision theory. Includes Monte Carlo and variati onal methods\, uncertainty quantification\, sequential models\, and princ ipled analysis of learning algorithms. Uncertainty is the organizing them e\, not just another application of general-purpose AI.\nAdditional topic s: Deep Representation Learning\, Reinforcement Learning\, Time Series & Sequential Data\, Explainability & Interpretability\, Robustness & Safety \nScope sources (2026): https://www.auai.org/uai2026/subject_areas\, http s://www.auai.org/uai2026/call_for_papers\nScope last checked: 2026-10-07 URL:https://www.auai.org/uai2026/ LOCATION:Amsterdam\, Netherlands END:VEVENT END:VCALENDAR