In this thesis we introduce and analyze the influence model, a particular but tractable mathematical representation of random, dynamical interactions on networks. Specifically, an influence modelâ€¦ (More)

Networks composed of a large number of parts interacting in structured waysâ€”yet with significant elements of uncertainty, randomness, and evolutionâ€”are ubiquitous and important in the natural worldâ€¦ (More)

This paper reports on preliminary explorations, both empirical and analytical, of probabilistic models of large-scale networks. We rst examine the structure of networks that grow by the addition ofâ€¦ (More)

Separable Bayesian Networks, or the Influence Model, are dynamic Bayesian Networks in which the conditional probability distribution can be separated into a function of only the marginal distributionâ€¦ (More)

This thesis involves designing discrete-time filters for modifying the spectrum of audio signals. The main contribution of this research is the significant reduction in the order of the filters. Toâ€¦ (More)