Date: July 2024
Course: Control and Machine Learning
Lecturer: Prof. Enrique Zuazua
Recordings
S01: Introduction to Control Theory
S02: Introduction: Calculus of Variations, Controllability and Optimal Design
S03: Introduction: Optimization and Perpectives
S04: Finite-dimensional Control Systems (1)
S05: Finite-dimensional Control Systems (2) and Gradient-descent methods (1)
S06: Gradient-descent methods (2), Duality algorithms, and Controllability (1)
S07: Controllability (2)
S08: Neural transport equations and infinite-dimensional control systems
S09: Wave equation control systems
S10: Momentum Neural ODE and Wave equation with viscous damping
S11: Heat and wave equations: Control systems and Turnpike principle (1)
S12: Turnpike principle (2), Deep Neural and Collective-dynamics
Topics
Watch the complete course @YouTube
S01: Introduction to Control Theory
S02: Introduction: Calculus of Variations, Controllability and Optimal Design
S03: Introduction: Optimization and Perpectives
S04: Finite-dimensional Control Systems (1)
S05: Finite-dimensional Control Systems (2) and Gradient-descent methods (1)
S06: Gradient-descent methods (2), Duality algorithms, and Controllability (1)
S07: Controllability (2)
S08: Neural transport equations and infinite-dimensional control systems
S09: Wave equation control systems
S10: Momentum Neural ODE and Wave equation with viscous damping
S11: Heat and wave equations: Control systems and Turnpike principle (1)
S12: Turnpike principle (2), Deep Neural and Collective-dynamics
Watch the complete course @YouTube
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