Centrality measures allow to identify important nodes in networked systems. An open question in network theory is the empirical observation that a node’s centrality—whose computation requires ...

Probability theory is indispensable in computer science: It is at the core of artificial intelligence and machine learning, which require decision making under uncertainty. It is integral to CS theory ...

Everyone is different, and we all have our own unique quirks and idiosyncrasies that make us who we are. There are some of us, though, who get inordinately irked by things the vast majority don’t have ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demo of Poisson regression, where the goal is to predict a count of things arriving, such as the number of telephone calls ...

Reproducibility Repository accompanying the presentation Applying Adjoints Twice (repo link). Here, we exemplarily implement a inverse problem that (using adjoint approaches) can be implemented quite ...

ABSTRACT: Count data is almost always over-dispersed where the variance exceeds the mean. Several count data models have been proposed by researchers but the problem of over-dispersion still remains ...

For information on using the package, see the stable documentation. Use the in-development documentation for the version of the documentation, which contains the unreleased features. It mixes two ...

Dimension reduction on neural activity paves a way for unsupervised neural decoding by dissociating the measurement of internal neural state repetition from the measurement of external variable tuning ...

Abstract: New lower bounds on the total variation distance between the distribution of a sum of independent Bernoulli random variables and the Poisson random variable (with the same mean) are derived ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted. Auxetics are ...