Explores the Eigenstate Thermalization Hypothesis in quantum systems, emphasizing the random matrix theory and the behavior of observables in thermal equilibrium.
Covers the AMP algorithm for spiked matrix estimation and its application to low-rank matrix factorization and GLM models.
Explores RRQR, TCS, tradeoffs, accuracy metrics, and low-rank matrix factorization frameworks, emphasizing communication avoidance and recent developments.
Covers image processing techniques including noise addition, filtering, and image enhancement using various filters and tools.
Covers the concept of sparse regression and the use of Gaussian additive noise in the context of MAP estimator and regularization.
Covers Gaussian random variables, affine transformations, and linear systems driven by Gaussian noise in multivariable control.
Covers Gaussian noise and decision-making in communication systems, emphasizing the importance of understanding Gaussian noise in signal processing.
Covers the Finite Element Method, discussing the derivation of the equation of motion and exploring mass and stiffness matrices.
Covers the derivation of the equation of motion, interpolation, Newton's equation, and energy conservation in finite element modeling.
