This set of lectures is an introduction to the stochastic analysis of Markov jump processes with applications in biology. The goal is of using stochastic calculus in this context, the analogue of Itô’s calculus for Brownian motion, as an efficient … Read more
This set of lectures is an introduction to the stochastic analysis of Markov jump processes with applications in biology. The goal is of using stochastic calculus in this context, the analogue of Itô’s calculus for Brownian motion, as an efficient … Read more
This set of lectures is an introduction to the stochastic analysis of Markov jump processes with applications in biology. The goal is of using stochastic calculus in this context, the analogue of Itô’s calculus for Brownian motion, as an efficient … Read more
This set of lectures is an introduction to the stochastic analysis of Markov jump processes with applications in biology. The goal is of using stochastic calculus in this context, the analogue of Itô’s calculus for Brownian motion, as an efficient … Read more
Each semester the RTG program will host a luncheon for women trainees with a faculty role model, from within or outside UNC, to share and discuss unique challenges, experiences, and opportunities for women in STEM. This semester the luncheon will … Read more
Multivariate Power Laws and Preferential Attachment Modeling In one-dimension, heavy tails or power-laws are easily understood to represent Pareto like behavior where data plotted on a log-log scale looks roughly linear. The generalization to higher dimensions is not always obvious … Read more
Multivariate Power Laws and Preferential Attachment Modeling In one-dimension, heavy tails or power-laws are easily understood to represent Pareto like behavior where data plotted on a log-log scale looks roughly linear. The generalization to higher dimensions is not always obvious … Read more
Multivariate Power Laws and Preferential Attachment Modeling In one-dimension, heavy tails or power-laws are easily understood to represent Pareto like behavior where data plotted on a log-log scale looks roughly linear. The generalization to higher dimensions is not always obvious … Read more
Multivariate Power Laws and Preferential Attachment Modeling In one-dimension, heavy tails or power-laws are easily understood to represent Pareto like behavior where data plotted on a log-log scale looks roughly linear. The generalization to higher dimensions is not always obvious … Read more
Multivariate Power Laws and Preferential Attachment Modeling In one-dimension, heavy tails or power-laws are easily understood to represent Pareto like behavior where data plotted on a log-log scale looks roughly linear. The generalization to higher dimensions is not always obvious … Read more
Multivariate Power Laws and Preferential Attachment Modeling In one-dimension, heavy tails or power-laws are easily understood to represent Pareto like behavior where data plotted on a log-log scale looks roughly linear. The generalization to higher dimensions is not always obvious … Read more
