Identifiable Representation Learning (26w5622)

The Banff International Research Station will host the "Identifiable Representation Learning" workshop in Banff from October 18 - 23, 2026.

Representation learning is at the heart of a paradigm shift in machine learning, driving many of today’s most advanced artificial intelligence (AI) systems. Representation learning transforms raw data into meaningful features that machines can use to perform a wide range of tasks, such as image recognition, content recommendation, and text generation. However, a key challenge remains: ensuring that these representations are identifiable, a property that is fundamental to reliably deploying AI systems in real-world applications. Although identifiability is critical to developing trustworthy AI systems, the current mathematical understanding of representation learning in general, and identifiability in particular, is extremely limited.

To address this gap in understanding, Banff International Research Station will host a workshop focusing on principled approaches for learning identifiable representations and understanding the properties of such representations. The event will feature leading experts in AI and machine learning, shaping the future direction of this critical area, uncovering its applications to scientific fields such as biology and neuroscience, and training the next generation of AI pioneers. By bringing together prominent researchers in the field, this workshop will play a pivotal role in advancing machine learning technologies, ensuring that AI systems are not only powerful, but that they are also reliable and robust in real-world settings.