Overview
The Workshop on Uncertainty in Machine Learning (WUML 2026) is scheduled to take place from February 2 to 4, 2026, at the University of Tartu in Estonia. This event continues the tradition of previous successful workshops held in Ghent, Munich, and Milan, providing a platform for researchers to engage in discussions about recent advancements and challenges in the domain of uncertainty in machine learning.
Background & Relevance
Uncertainty in machine learning is a critical area of research that addresses how models can quantify and manage uncertainty in predictions. This field is increasingly important as machine learning applications expand into high-stakes domains such as healthcare, finance, and autonomous systems. The workshop aims to foster collaboration and innovation by bringing together researchers who are exploring new methodologies and applications related to uncertainty.
Key Details
- Dates: February 2–4, 2026
- Location: University of Tartu, Estonia
- Keynote Speakers:
- Willem Waegeman (Ghent University)
- Ilja Kuzborskij (Google DeepMind)
- Invited talk by Arun Kumar Singh (University of Tartu)
- Participation Fee: Free (attendees cover their own travel and accommodation)
- Capacity: Limited to 150 participants
- Preliminary Information: WUML 2026 Website
- RSVP Deadline: January 7, 2026, via Attendance Form
Eligibility & Participation
The workshop is open to all researchers and practitioners interested in the topic of uncertainty in machine learning. Participants are encouraged to engage actively, whether by presenting a talk, showcasing a poster, or simply attending the sessions. This informal format is designed to facilitate open discussions and networking among attendees.
Submission or Application Guidelines
To confirm attendance, interested participants must complete the RSVP form by January 7, 2026. Given the limited capacity, early registration is recommended to secure a spot at the workshop.
More Information
The exploration of uncertainty in machine learning is vital for enhancing model reliability and performance. As machine learning systems are deployed in more complex and critical environments, understanding and managing uncertainty becomes essential. Workshops like WUML 2026 play a significant role in advancing research and fostering collaboration among experts in this field.
Conclusion
WUML 2026 promises to be an engaging and insightful event for those interested in the complexities of uncertainty in machine learning. Researchers are encouraged to participate, share their insights, and connect with peers in this evolving area of study. Mark your calendars and prepare to join the conversation in Tartu!
Category: Conferences & Workshops
Tags: uncertainty in machine learning, machine learning, workshop, University of Tartu, ML, AI, Willem Waegeman, Ilja Kuzborskij, Arun Kumar Singh, research forum, poster presentation, keynote talks
