About the Workshop

Following the success of the Dagstuhl Seminar in 2024, this focused workshop on "Rethinking the Role of Bayesianism in the Age of Modern AI" will take place from October 27 to 31, 2025. The gathering will bring together researchers exploring the frontiers of Bayesian Machine Learning and Deep Learning in a collaborative atmosphere.

Despite the recent success of large-scale deep learning, these systems still fall short in terms of their reliability and trustworthiness. They often lack the ability to estimate their own uncertainty in a calibrated way, encode meaningful prior knowledge, avoid catastrophic failures, and reason about their environments to avoid such failures.

Bayesian deep learning (BDL) has harbored the promise of achieving these desiderata by combining the statistical foundations of Bayesian inference with the practically successful engineering solutions of deep learning methods. However, compared to its promise, BDL methods often do not live up to expectations in terms of real-world impact.

This workshop aims to rethink and redefine the promises and challenges of Bayesian approaches; elucidate which Bayesian methods might prevail against their non-Bayesian competitors; and identify key application areas where Bayes can shine. The event is planned as a small, discussion-driven gathering with a relaxed and collaborative atmosphere, and is designed to encourage deep exchange, new ideas, and informal collaboration across intersecting areas of research.

Organizing Committee

Workshop Program

The workshop features a highly interactive program, focusing on active participation and discussion among participants. The schedule will include:

• Roundtable discussions on critical challenges in Bayesian AI
• Interactive breakout sessions
• Poster sessions and lightning talks
• Social activities, including a trip to the desert and other local attractions

A detailed program is available here: open the spreadsheet.