We desribe how we extend R with an external C++ code library by using the Rcpp package. Our working example uses the recent machine learning library and application ‘Corels’ providing optimal yet easily interpretable rule lists <arXiv:1704.01701> which we bring to R in the form of the ‘RcppCorels’ package. We discuss each step in the…
Empirical evidence, e.g. observed likelihood ratio, is an estimator of the difference of the divergences between two competing models (or, model sets) and the true generating mechanism. It is unclear how to use such empirical evidence in scientific practice. Scientists usually want to know “how often would I get this level of evidence”. The answer…
Adverse drug-drug interactions (DDIs) remain a leading cause of morbidity and mortality. Identifying potential DDIs during the drug design process is critical for patients and society. Although several computational models have been proposed for DDI prediction, there are still limitations: (1) specialized design of drug representation for DDI predictions is lacking; (2) predictions are based…
In diverse biological applications, particle tracking of passive microscopic species has become the experimental measurement of choice — when either the materials are of limited volume, or so soft as to deform uncontrollably when manipulated by traditional instruments. In a wide range of particle tracking experiments, a ubiquitous finding is that the mean squared displacement…
In this article, I first review preliminaries of point particle mechanics, introduce the nature and role of the constraint of a mechanical system, and the nature of Killing vectors as explicit symmetry of a geodesic. Then, starting from a general Randers-Finsler spacetime, I describe how the Jacobi-Maupertuis and Eisenhart lift formulations produce a different Rander-…
We started with a knowledge graph of connected entities and descriptive properties of those entities, from which, a hierarchical representation of the knowledge graph is derived. Using a graphical, energy-based neural network, we are able to show that the structure of the hierarchy can be internally captured by the neural network, which allows for efficient…
For every finitary monad $T$ on sets and every endofunctor $F$ on the category of $T$-algebras we introduce the concept of an ffg-Elgot algebra for $F$, that is, an algebra admitting coherent solutions for finite systems of recursive equations with effects represented by the monad $T$. The goal is to study the existence and construction…
The seminal papers of Pickands [1,2] paved the way for a systematic study of high exceedance probabilities of both stationary and non-stationary Gaussian processes. Yet, in the vector-valued setting, due to the lack of key tools including Slepian’s Lemma, Borell-TIS and Piterbarg inequalities there has not been any methodological development in the literature for the…
Mixing is an omnipresent process in a wide-range of industrial applications, which supports scientific efforts to devise techniques for optimising mixing processes under time and energy constraints. In this endeavor, we present a computational framework based on nonlinear direct-adjoint looping for the enhancement of mixing efficiency in a binary fluid system. The governing equations consist…
We develop a mathematically rigorous theory for the quantum transfer processes in degenerate donor-acceptor dimers in contact with a thermal environment. We calculate explicitly the transfer rates and the acceptor population efficiency. The latter depends critically on the initial donor state. We show that quantum coherence in the initial state enhances the transfer process. If…