Despite their diverse origin, networks of large real-world systems reveal a number of common properties including small-world phenomena, scale-free degree distributions and modularity. Recently, network self-similarity as a natural outcome of the evolution of real-world systems has also attracted much attention within the physics literature. Here we investigate the scaling of density in complex...

We introduce RNADE, a new model for joint density estimation of real-valued vectors. Our model calculates the density of a datapoint as the product of onedimensional conditionals modeled using mixture density networks with shared parameters. RNADE learns a distributed representation of the data, while having a tractable expression for the calculation of densities. A tractable likelihood allows ...

The spatial density of false measurements is known as clutter density in signal and data processing of targets. It is unknown in practice and its knowledge has a significant impact on the effective processing of target information. This paper presents in the first time a number of theoretically solid estimators for clutter density based on conditional mean, maximum likelihood, and method of mom...

It is a natural problem to investigate the set of what we will call exceptional points for S, i.e. points which are neither density points of S, nor those of R\S. Note that this is a topological notion, since as far as measure theory is concerned, there are no such exceptional points. First, we quantify the notion of exceptional point: given a measurable S ⊂ R and 0 ≤ δ ≤ 1/2, we will call p ∈ ...

We report a first-principles computational method to describe many-electron dynamics in crystalline solids. The method is based on the time-dependent density functional theory, solving the time-dependent Kohn-Sham equation in real time and real space. The calculation is efficiently parallelized by distributing computations of different k-points among processors. To illustrate the usefulness of ...

The Polarizable Continuum Model (PCM) can be used in conjunction with Density Functional Theory (DFT) and its time-dependent extension (TDDFT) to simulate the electronic and optical properties of molecules and nanoparticles immersed in a dielectric environment, typically liquid solvents. In this contribution, we develop a methodology to account for solvation effects in real-space (and real-time...

The real-time performance of a fundamental frequency estimation algorithm depends not only on its computational eeciency but also on its ability to obtain accurate estimates from short signal segments. Previous frequency-domain algorithms make use of spectral analysis algorithms that require the application of a window function, which cause them to fail when signal segments are short and their ...

The practice of fine frequency estimation of a single tone using the three samples around the DFT output maximizer has progressed steadily over the preceding decades. A number of authors built on the early work of Kay, Rife and Boorstyn, et al. In the middle 1990s Quinn's estimators were considered superior, but were computationally expensive for real-time processors of the day. MacLeod and Jac...

The density and duration of pneumococcal carriage are considered to affect the likelihood of transmission and invasive disease. Because of its importance in both spreading and causing disease, carriage has been suggested as an endpoint in future vaccine studies. Culture is the current gold standard for detection, but may not be sensitive enough to detect changes at low density. Healthy adult vo...

This paper illustrates how to compare different agent-based models and how to compare an agent-based model with real data. As examples we investigate ARFIMA models, the probability density function, and the spectral density function. We illustrate the methodology in an analysis of the agent-based model developed by Levy, Levy, Solomon (2000), and confront it with the S&P 500 for a comparison wi...