Applications of GAMPDelves into applying the GAMP algorithm to simplify the lasso problem and analyze optimization challenges in neural networks.
Evolution of Density MatricesExplores the evolution of density matrices in quantum optics, emphasizing super-operators and completely positive maps.
Linear Models: BasicsIntroduces linear models in machine learning, covering basics, parametric models, multi-output regression, and evaluation metrics.
Linear Regression BasicsCovers the basics of linear regression in machine learning, including model training, loss functions, and evaluation metrics.
Introduction to Quantum ChaosCovers the introduction to Quantum Chaos, classical chaos, sensitivity to initial conditions, ergodicity, and Lyapunov exponents.
Linear Regression: BasicsCovers the basics of linear regression, binary and multi-class classification, and evaluation metrics.
Quantum Physics IExplores quantum state evolution, unitary operators, Heisenberg representation, spin precession, and observable averages.