22 papers · ranked by Valyu relevance
Harlan Campbell, Tim P. Morris, Paul Gustafson
Derived variables are variables that are constructed from one or more source variables through established mathematical operations or algorithms. For example, body mass index (BMI) is a derived variable constructed from two source variables: weight and height. When using a derived variable as the outcome in a…
Laurie Berrie, Kellyn F Arnold, Georgia D Tomova, Mark S Gilthorpe + 1 more
'Peter W G Tennant'] Title: Abstract Deterministic variables are variables that are functionally determined by one or more parent variables. They commonly arise when a variable has been functionally created from one or more parent variables, as with derived variables, and in compositional data, where the “whole”…
Amir Shaikhha, Mathieu Huot, Shabnam Ghasemirad, Andrew Fitzgibbon + 2 more
'Simon Peyton Jones' 'Dimitrios Vytiniotis'] Automatic differentiation (AD) is a technique for computing the derivative of a function represented by a program. This technique is considered as the de-facto standard for computing the differentiation in many machine learning and optimisation software tools. Despite the…
Emanuele Guidotti
The R package calculus implements C++ optimized functions for numerical and symbolic calculus, such as the Einstein summing convention, fast computation of the Levi-Civita symbol and generalized Kronecker delta, Taylor series expansion, multivariate Hermite polynomials, high-order derivatives, ordinary differential…
Pierre de Villemereuil, Holger Schielzeth, Shinichi Nakagawa, Michael Morrissey
'Michael Morrissey'] Methods for inference and interpretation of evolutionary quantitative genetic parameters, and for prediction of the response to selection, are best developed for traits with normal distributions. Many traits of evolutionary interest, including many life history and behavioral traits, have…
Duncan Bossion, Sutirtha Chowdhury, Pengfei Huo
We present the rigorous theoretical framework of the generalized spin mapping representation for non- adiabatic dynamics. This formalism is based on the generators of the su(N) Lie algebra to represent N discrete electronic states, thus preserving the size of the original Hilbert space in the state representation. The…
Maria Isabelle Fite, Jonathan Bartlett
Differential operators usually result in derivatives expressed as a ratio of differentials. For all but the simplest derivatives, these ratios are typically not algebraically manipulable, but must be held together as a unit in order to prevent contradictions. However, this is primarily a notational and conceptual…
Drosos Kourounis, Leonidas N. Gergidis, Michael A. Saunders, Andrea Walther + 1 more
'Andrea Walther' 'Olaf Schenk'] Template metaprogramming is a popular technique for implementing compile time mechanisms for numerical computing. We demonstrate how expression templates can be used for compile time symbolic differentiation of algebraic expressions in C++ computer programs. Given a positive integer N…
Louise A C Millard, Nashita Patel, Kate Tilling, Melanie Lewcock + 2 more
Continuous glucose monitors (CGM) record interstitial glucose ‘continuously’, producing a sequence of measurements for each participant (e.g. the average glucose every 5 minutes over several days, both day and night). To analyze these data, researchers tend to derive summary variables such as the Area Under the Curve…
Matieyendou Lamboni
Mathematical models are sometime given as functions of independent input variables and equations or inequations connecting the input variables. A probabilistic characterization of such models results in treating them as functions with non-independent variables. Using the distribution function or copula of such…
Ronald Mahler
The finite-set statistics (FISST) foundational approach to multitarget tracking and information fusion was introduced in the mid-1990s and extended in 2001. FISST was devised to be as “engineering-friendly” as possible by avoiding avoidable mathematical abstraction and complexity-and, especially, by avoiding measure…
Authors not listed
Deriving versatile and robust mechanistic models from experimental data is a key challenge in engineering and natural sciences. This is especially true in chemical reaction engineering, where reactor manufacturers and operators increasingly pursue the development and maintenance of digital twins that rely on frequent…
Rachel Mester, Alfonso Landeros, Chris Rackauckas, Kenneth Lange + 1 more
Differential sensitivity analysis is indispensable in fitting parameters, understanding uncertainty, and forecasting the results of both thought and lab experiments. Although there are many methods currently available for performing differential sensitivity analysis of biological models, it can be difficult to…
Michael B. Morrissey, Jonathan M. Henshaw
When environmental variation contributes to relationships between traits and fitness, it can confound analyses of phenotypic selection and, ultimately, bias predictions of adaptive evolution. To date, discussions of how to combat this problem emphasise complex statistical analyses aimed at estimating the genetic basis…
Scott A. Malec, Sanya B. Taneja, Steven M. Albert, C. Elizabeth Shaaban + 5 more
Causal feature selection is essential for estimating effects from observational data. Identifying confounders is a crucial step in this process. Traditionally, researchers employ content-matter expertise and literature review to identify confounders. Uncontrolled confounding from unidentified confounders threatens…
Charles C. Margossian, Michael Betancourt
Derivative-based algorithms are ubiquitous in statistics, machine learning, and applied mathematics. Automatic differentiation offers an algorithmic way to efficiently evaluate these derivatives from computer programs that execute relevant functions. Implementing automatic differentiation for programs that incorporate…
Authors not listed
We present a novel, flexible framework for electronic structure interfaces designed for nonadiabatic dynamics simulations, implemented in Python 3 using concepts of object-oriented programming. This framework streamlines the development of new interfaces by providing a reusable and extendable code base. It supports the…
Haipeng Yu, Gota Morota
Genetic connectedness is a critical component of genetic evaluation as it assesses the comparability of predicted genetic values across units. Genetic connectedness also plays an essential role in quantifying the linkage between reference and validation sets in whole-genome prediction. Despite its importance, there is…
Marcus Christian Lehmann, Mirsad Hadžiefendić, Albert Piwonski, Rolf Schuhmann
'Rolf Schuhmann'] Electromagnetic phenomena are mathematically described by solutions of boundary value problems. For exploiting symmetries of these boundary value problems in a way that is offered by techniques of dimensional reduction, it needs to be justified that the derivative in symmetry direction is constant or…
Sara Giarrusso, Paola Gori-Giorgi, Federica Agostini
We generalize the definitions of local scalar potentials named vkin and vN−1, which are relevant to properly describe phenomena such as molecular dissociation with density-functional theory, to the case in which the electronic wavefunction corresponds to a complex current-carrying state. In such a case, an extra term…
Authors not listed
This paper presents the Multi Cell-line Kinetic Model (MCKM), a novel generalised kinetic mechanistic model specifically tailored for Ambr15™ fed-batch cultivations of multiple Chinese Hamster Ovary (CHO) cell lines producing different recombinant monoclonal antibodies (mAbs). Unlike traditional models that requires…
Caroline E. Thomson, Isabel S. Winney, Oceane C. Salles, Benoit Pujol
Non-genetic influences on phenotypic traits can affect our interpretation of genetic variance and the evolutionary potential of populations to respond to selection, with consequences for our ability to predict the outcomes of selection. Long-term population surveys and experiments have shown that quantitative genetic…