Koopman Operator Theory Based Machine Learning of Dynamical Systems, Igor Mezic

Koopman Operator Theory Based Machine Learning of Dynamical Systems, Igor Mezic
Share:

Download MP3


Similar Tracks

Linear Stochastic Graphon Systems with Q-Noise, Alex Dunyak GERAD Recherche
Koopman Spectral Analysis (Overview) Steve Brunton
The Operator is the Model Fields Institute
Dynamic Mode Decomposition from Koopman Theory to Applications (Prof. Peter J. Schmid) von Karman Institute for Fluid Dynamics
Data-driven model discovery: Targeted use of deep neural networks for physics and engineering Nathan Kutz
ME203Lecture1:Introduction Igor Mezic
30 Minutes With Holy Spirit: Deep Prayer & Prophetic Worship Music DappyTKeys
Transformers (how LLMs work) explained visually | DL5 3Blue1Brown
Dynamic Mode Decomposition (Overview) Steve Brunton
MIT Robotics - Harry Asada - Koopman Lifting Linearization for Global, Unified Representation ... MIT Robotics
Physics-informed neural networks (PINNs) LIDA - Leeds Institute for Data Analytics -
Understanding Thermal Radiation The Efficient Engineer
Understanding Vibration and Resonance The Efficient Engineer
Nathan Kutz - The Dynamic Mode Decomposition - A Data-Driven Algorithm The Alan Turing Institute
Reinforcement Learning: Machine Learning Meets Control Theory Steve Brunton
Algebra - How To Solve Equations Quickly! The Organic Chemistry Tutor
Koopman Theory + Embeddings Nathan Kutz
Jason Choi -- Introduction to Control Lyapunov Functions and Control Barrier Functions UCSD Safe Autonomous Systems Lab
NeurIPS 2020 Tutorial: Deep Implicit Layers Zico Kolter
The Anatomy of a Dynamical System Steve Brunton