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The full-day workshop will be organized in a classroom-like experience starting with lectures on physics-informed learning and control in the morning, followed by step-by-step tutorials, and finally finished by 1-2 hour supervised audience work on a few simple assignments.
Tentative Schedule
09:00 - 09:10
Warming up: Welcome, motivation, and introduction
Warming up: Welcome, motivation, and introduction
09:15 - 10:00
Combining model-based and data-driven models: an application to synthetic biology resource competition
Combining model-based and data-driven models: an application to synthetic biology resource competition
Eduardo Sontag (Northeastern University)
10:00 - 10:45
Integrating Physics in Gaussian Process and Neural-Networks for Model Based Control
Integrating Physics in Gaussian Process and Neural-Networks for Model Based Control
Rolf Findeisen (TU Darmstadt)
Coffee Break 10:45 - 11:15
11:15 - 12:00
Learning Dynamical System Models with Physical Priors
Learning Dynamical System Models with Physical Priors
Thomas Beckers (Vanderbilt University)
12:00 - 12:45
Physics-informed Learning and Control with Gaussian Processes and its Application to Robotics
Physics-informed Learning and Control with Gaussian Processes and its Application to Robotics
Sandra Hirche (Technical University of Munich)
Lunch Break 12:45 - 02:00
02:00 - 02:40
Coding Tutorial I
Coding Tutorial I
Ján Drgoňa (Johns Hopkins University)
02:40 - 03:15
Coding Tutorial II
Coding Tutorial II
TBA
Coffee Break 03:15 - 03:45
03:45 - 05:15
Coding Assignments
Coding Assignments
05:15 - 05:30
Closing remarks / discussion
Closing remarks / discussion
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