Neural networks under SGDExplores the optimization of neural networks using Stochastic Gradient Descent (SGD) and the concept of dual risk versus empirical risk.
Information Measures: Part 2Covers information measures like entropy, joint entropy, and mutual information in information theory and data processing.
Symmetries and Conservation LawsCovers symmetries and conservation laws in fluid dynamics, emphasizing the importance of maximizing symmetries in ideal fluid systems.
Gradient, divergenceCovers the definitions of gradient and divergence, including the Cartesian coordinate system and the divergence theorem.
Vector Analysis ReviewCovers unit vectors, coordinate system conversion, divergence, and rotational concepts in vector analysis.
