Joel Nishimura

TL;DR: Random graph null models have found widespread application in diverse research communities analyzing network datasets, including social, information, and economic networks, as well as food webs, pr....

TL;DR: This work introduces restreaming graph partitioning and develops algorithms that scale similarly to streaming partitioning algorithms yet empirically perform as well as fully offline algorithms.

TL;DR: This work studies the subtle but important decisions underlying the specification of a configuration model, and investigates the role these choices play in graph sampling procedures and a suite of applications, placing particular emphasis on the importance of specifying the appropriate graph labeling under which to consider a null model.

TL;DR: It is shown that for pulse-coupled oscillators a class of phase response curves with both excitation and inhibition exhibit robust convergence to synchrony on arbitrary aperiodic connected graphs with delays.

TL;DR: These results suggest methods for the analysis of pulse-coupled oscillators, and provide insights into the balance of excitation and inhibition in the operation of biological type-II phase response curves and also the design of decentralized and minimal clock synchronization schemes in sensor nets.