We develop geometric dynamical systems methods to determine how various components contribute to a neuronal network's emergent population behavior. The results clarify the mu...
In this paper, we model the pair-wise similarities of a set of documents as a weighted network with a single cutoff parameter. Such a network can be thought of an ensemble of unwe...
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
e for abstract modeling, algorithmic design and analysis to achieve provably efficient, scalable and fault-tolerant realizations of such huge, highly-dynamic, complex, non-conventi...
The diffusion of innovations has long been a research domain in IS research. Yet, there is no sound theory nor practice to fully understand the complex mechanisms behind networks ...