In-Context Operator Networks - Towards Large Scientific Learning Models - Stanley Osher

Explore the cutting-edge research on In-Context Operator Networks (ICON) and their potential for large scientific learning models in this 30-minute conference talk by Stanley Osher from UCLA. Recorded as part of the Interfaces and Mixing in Fluids, Plasmas, and Materials conference at the Kavli Institute for Theoretical Physics, delve into the intersection of quantum metrology, fundamental physics, and advanced computational methods. Discover how ICON contributes to various scientific fields, including dark matter searches and gravitational wave detection. Gain insights into the unexpected connections between quantum metrology methods and diverse areas of physics, fostering cross-disciplinary collaboration and innovation. Learn about the latest developments in precision quantum metrology and its applications in particle physics, condensed matter, atomic physics, and quantum information. Understand the importance of bridging theory and experiment across different research areas to drive new scientific discoveries and advance our understanding of fundamental physics.

In-Context Operator Networks (ICON): Towards Large Scientific Learning Models ▸ Stanley Osher (UCLA)