Covers percolation theory, absorbed polymers, giant molecules, phase transition, scaling assumptions, and universal behavior in percolation models.
Delves into centrality and hubs in network neuroscience, exploring node importance, small-world networks, brain structural connectome, and percolation theory.
Explores broken and emerging symmetries in turbulent states, discussing energy cascades, lack of scale invariance, and potential conformal invariance.
Explores continuous random variables, density functions, joint variables, independence, and conditional densities.
Explores renormalization, scaling, critical points, exponents, and phase transitions in conformal field theory and quantum gravity.
Covers fundamental concepts in probability and statistics, emphasizing data analysis techniques and statistical modeling.
Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.
Explores centrality, hubs, eigenvectors, clustering coefficients, small-world networks, network failures, and percolation theory in brain networks.
