Information-Theoretic Methods for Learning Dynamics

Workshop bringing together researchers working on AI for learning dynamics from data, with a special focus on information-theoretic methods. Topics include predictive information, the information bottleneck, latent-variable models, entropy and mutual-information estimation, world models of biological systems, and connections to dynamical systems and control theory. The workshop is part of the six-week NITMB program “Image-Based Scientific Machine Learning for Theories of Biological Dynamics Across Scales” (February 1–March 12, 2027).

Program: AI in Biological Dynamics Scientific Focus — details for the six-week NITMB program: https://www.nitmb.org/ai-in-biological-dynamics-scientific-focus

Application deadlines: November 9, 2026 for applicants requesting travel and lodging support; December 8, 2026 for local applicants. Students, postdocs and early-career researchers are encouraged to apply. See the Application tab on the workshop website.