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Most particle induced X-ray emission (PIXE) data analysis codes are not focused on handling multilayered samples. We have developed an open-source library called "LibCPIXE", for PIXE data analysis. It is written in standard C and implements…

Materials Science · Physics 2007-07-18 C. Pascual-Izarra , N. P. Barradas , M. A. Reis

We present a novel programming language design that attempts to combine the clarity and safety of high-level functional languages with the efficiency and parallelism of low-level numerical languages. We treat arrays as eagerly-memoized…

Numerical simulations are ubiquitous in mathematics and computational science. Several industrial and clinical applications entail modeling complex multiphysics systems that evolve over a variety of spatial and temporal scales. This study…

Mathematical Software · Computer Science 2022-11-14 Pasquale Claudio Africa

\texttt{Mixture-Models} is an open-source Python library for fitting Gaussian Mixture Models (GMM) and their variants, such as Parsimonious GMMs, Mixture of Factor Analyzers, MClust models, Mixture of Student's t distributions, etc. It…

Computation · Statistics 2024-02-19 Siva Rajesh Kasa , Hu Yijie , Santhosh Kumar Kasa , Vaibhav Rajan

A standard practice in extragalactic population studies is the fitting of parametric models to galaxy images. From such fits, key structural parameters of galaxies such as total flux and effective radius (size) can be extracted. One of the…

Astrophysics of Galaxies · Physics 2023-06-12 Imad Pasha , Tim B. Miller

Modal methods for simulating vibrations of strings, membranes, and plates are widely used in acoustics and physically informed audio synthesis. However, traditional implementations, particularly for non-linear models like the von K\'arm\'an…

Sound · Computer Science 2025-05-27 Rodrigo Diaz , Mark Sandler

NIFTY, "Numerical Information Field Theory", is a software package designed to enable the development of signal inference algorithms that operate regardless of the underlying spatial grid and its resolution. Its object-oriented framework is…

Instrumentation and Methods for Astrophysics · Physics 2013-06-06 Marco Selig , Michael R. Bell , Henrik Junklewitz , Niels Oppermann , Martin Reinecke , Maksim Greiner , Carlos Pachajoa , Torsten A. Enßlin

The R package merlin performs flexible joint modelling of hierarchical multi-outcome data. Increasingly, multiple longitudinal biomarker measurements, possibly censored time-to-event outcomes and baseline characteristics are available.…

Computation · Statistics 2020-07-29 Emma C. Martin , Alessandro Gasparini , Michael J. Crowther

Julia is a mature general-purpose programming language, with a large ecosystem of libraries and more than 12000 third-party packages, which specifically targets scientific computing. As a language, Julia is as dynamic, interactive, and…

Modular programming is a development paradigm that emphasizes self-contained, flexible, and independent pieces of functionality. This practice allows new features to be seamlessly added when desired, and unwanted features to be removed,…

Other Statistics · Statistics 2016-10-24 Eric Hare , Andee Kaplan

Event reweighting has been implemented in the NuWro neutrino event generator for a number of free theory parameters in the interaction model. Event reweighting is a key analysis technique, used to efficiently study the effect of neutrino…

High Energy Physics - Experiment · Physics 2017-10-11 Luke Pickering , Patrick Stowell , Jan Sobczyk

JuMP is an open-source modeling language that allows users to express a wide range of optimization problems (linear, mixed-integer, quadratic, conic-quadratic, semidefinite, and nonlinear) in a high-level, algebraic syntax. JuMP takes…

Optimization and Control · Mathematics 2017-05-08 Iain Dunning , Joey Huchette , Miles Lubin

Inference algorithms for probabilistic programming are complex imperative programs with many moving parts. Efficient inference often requires customising an algorithm to a particular probabilistic model or problem, sometimes called…

Programming Languages · Computer Science 2024-12-24 Minh Nguyen , Roly Perera , Meng Wang , Steven Ramsay

The use of Bayesian adaptive designs for randomised controlled trials has been hindered by the lack of software readily available to statisticians. We have developed a new software package (Bayesian Adaptive Trials Simulator Software -…

Linguistic style is pivotal for understanding how texts convey meaning and fulfill communicative purposes, yet extracting detailed stylistic features at scale remains challenging. We present Neurobiber, a transformer-based system for fast,…

Computation and Language · Computer Science 2025-02-27 Kenan Alkiek , Anna Wegmann , Jian Zhu , David Jurgens

This paper describes a C++ library that compiles neural network models at runtime into machine code that performs inference. This approach in general promises to achieve the best performance possible since it is able to integrate statically…

Machine Learning · Computer Science 2019-12-23 Felix Thielke , Arne Hasselbring

GPUs and other accelerators are popular devices for accelerating compute-intensive, parallelizable applications. However, programming these devices is a difficult task. Writing efficient device code is challenging, and is typically done in…

Programming Languages · Computer Science 2018-10-23 Tim Besard , Christophe Foket , Bjorn De Sutter

ESCAPE is a free python package and framework for creating applications for simulating and fitting of X-ray and neutron scattering data with current support for specular reflectivity, polarized neutron reflectometry, high resolution X-ray…

Computational Engineering, Finance, and Science · Computer Science 2020-11-11 Denis Korolkov , Stepan Rakhimov

Writing high-performance code requires significant expertise in the programming language, compiler optimizations, and hardware knowledge. This often leads to poor productivity and portability and is inconvenient for a non-programmer…

Performance · Computer Science 2020-09-01 Ajitesh Srivastava , Naifeng Zhang , Rajgopal Kannan , Viktor K. Prasanna

In reinforcement learning, wrappers are universally used to transform the information that passes between a model and an environment. Despite their ubiquity, no library exists with reasonable implementations of all popular preprocessing…

Machine Learning · Computer Science 2021-11-17 J. K. Terry , Benjamin Black , Ananth Hari