Professor Stefan Sommer, PhD student Libby Baker and Abel Verley, Master student intern to Stochastic Morphometry project, participated in four-day G-StAI workshop, May 6-9 in Lesbos, Greece, aimed at researchers working in geometric statistics and geometric methods for deep learning.
The center is located in a former Greek monastery and allows for a relaxing atmosphere for you to collaborate or be alone with your thoughts and focus on writing.
The aim with the workshop was to bring together experts on differential geometry, geometric statistics and deep learning to spawn discussion across these fields. In several important areas, using geometric ideas in machine learning and deep learning has lately proved extremely useful, for example for deep learning on Lie groups and manifolds, for equivariant networks, and for latent representations with non-Euclidean spaces. Conversely, machine learning gives new applications and insight in geometry with examples being the theoretical interest in optimal transport and relaxed versions of this, and the use of neural networks to learn stochastic dynamics and scores on geometric spaces.
With the workshop, participants had the possibility to meet top experts from geometry, geometric statistics and machine learning together in a small workshop format setting with informal discussions that lead to new ideas, new collaborations and new results.
