Explores diffusion models, focusing on generating samples from a distribution and the importance of denoising in the process.
Explores the benefits of deeper networks in deep learning and the importance of over-parameterization and generalization.
Explores beams with distributed loads and their differential relations between shear force and bending moment.
Covers the concept of compression and constructing prefix-free codes based on given information.
Covers the concepts of compression and prediction using prefix-free codes and distributions.
