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We present the software library libCreme which we have previously used to successfully calculate convex-roof entanglement measures of mixed quantum states appearing in realistic physical systems. Evaluating the amount of entanglement in…

Quantum Physics · Physics 2015-05-28 Beat Röthlisberger , Jörg Lehmann , Daniel Loss

Cloud platforms allow users to execute tasks directly from their web browser and are a key enabling technology not only for commerce but also for computational science. Research software is often developed by scientists with limited…

This paper describes mathlib, a community-driven effort to build a unified library of mathematics formalized in the Lean proof assistant. Among proof assistant libraries, it is distinguished by its dependently typed foundations, focus on…

Logic in Computer Science · Computer Science 2020-01-28 The mathlib Community

We present the Julia package Manifolds$.$jl, providing a fast and easy-to-use library of Riemannian manifolds and Lie groups. This package enables working with data defined on a Riemannian manifold, such as the circle, the sphere, symmetric…

Mathematical Software · Computer Science 2025-05-20 Seth D. Axen , Mateusz Baran , Ronny Bergmann , Krzysztof Rzecki

Tracing - estimating the spatial state of - long deformable linear objects such as cables, threads, hoses, or ropes, is useful for a broad range of tasks in homes, retail, factories, construction, transportation, and healthcare. For long…

Summary Brain Predictability toolbox (BPt) represents a unified framework of machine learning (ML) tools designed to work with both tabulated data (in particular brain, psychiatric, behavioral, and physiological variables) and neuroimaging…

Machine Learning · Computer Science 2020-11-04 Sage Hahn , Dekang Yuan , Wesley Thompson , Max M Owens , Nicholas Allgaier , Hugh Garavan

This paper presents a new Matlab toolbox, aimed at facilitating the use of polynomial optimization for stability analysis of nonlinear systems. In the past decade several decisive contributions made it possible to recast this type of…

Optimization and Control · Mathematics 2024-04-03 Stéphane Drobot , Matteo Tacchi , Carmen Cardozo , Colin N. Jones

The Matlab toolbox SciXMiner is designed for the visualization and analysis of time series and features with a special focus to classification problems. It was developed at the Institute of Applied Computer Science of the Karlsruhe…

Interested in formalizing the generation of fast running code for linear algebra applications, the authors show how an index-free, calculational approach to matrix algebra can be developed by regarding matrices as morphisms of a category…

Software Engineering · Computer Science 2013-12-18 Hugo Daniel Macedo , José N. Oliveira

Apache Spark is a popular open-source platform for large-scale data processing that is well-suited for iterative machine learning tasks. In this paper we present MLlib, Spark's open-source distributed machine learning library. MLlib…

Algorithm portfolio and selection approaches have achieved remarkable improvements over single solvers. However, the implementation of such systems is often highly customised and specific to the problem domain. This makes it difficult for…

Artificial Intelligence · Computer Science 2014-05-01 Lars Kotthoff

Knots and links which are closed 3-braids are a very special class. Like 2-bridge knots and links, they are simple enough to admit a complete classification. At the same time they are rich enough to serve as a source of examples on which,…

Geometric Topology · Mathematics 2008-05-14 Joan S. Birman , William W. Menasco

DADApy is a python software package for analysing and characterising high-dimensional data manifolds. It provides methods for estimating the intrinsic dimension and the probability density, for performing density-based clustering and for…

In this paper we present MLaut (Machine Learning AUtomation Toolbox) for the python data science ecosystem. MLaut automates large-scale evaluation and benchmarking of machine learning algorithms on a large number of datasets. MLaut provides…

Machine Learning · Computer Science 2019-01-14 Viktor Kazakov , Franz J. Király

With the spreading prevalence of Big Data, many advances have recently been made in this field. Frameworks such as Apache Hadoop and Apache Spark have gained a lot of traction over the past decades and have become massively popular,…

Databases · Computer Science 2017-11-28 Anand Gupta , Hardeo Thakur , Ritvik Shrivastava , Pulkit Kumar , Sreyashi Nag

Mixed Integer Linear Programming (MILP) is a fundamental tool for modeling combinatorial optimization problems. Recently, a growing body of research has used machine learning to accelerate MILP solving. Despite the increasing popularity of…

Machine Learning · Computer Science 2024-10-29 Weimin Huang , Taoan Huang , Aaron M Ferber , Bistra Dilkina

We present TopoTB, a software package written in the Mathematica language, designed to compute electronic structures, topological properties, and phase diagrams based on tight-binding models. TopoTB is user-friendly, with an interactive…

Materials Science · Physics 2024-03-14 Xinliang Huang , Fawei Zheng , Ning Hao

LIBS2ML is a library based on scalable second order learning algorithms for solving large-scale problems, i.e., big data problems in machine learning. LIBS2ML has been developed using MEX files, i.e., C++ with MATLAB/Octave interface to…

Machine Learning · Computer Science 2021-11-16 Vinod Kumar Chauhan , Anuj Sharma , Kalpana Dahiya

The fitting or parameter estimation of complex ecological models is a challenging optimisation task, with a notable lack of tools for fitting complex, long runtime or stochastic models. calibrar is an R package that is dedicated to the…

Quantitative Methods · Quantitative Biology 2024-04-30 Ricardo Oliveros-Ramos , Yunne-Jai Shin

BondGraphTools is a Python library for scripted modelling of complex multi-physics systems. In contrast to existing modelling solutions, BondGraphTools is based upon the well established bond graph methodology, provides a programming…

Systems and Control · Electrical Eng. & Systems 2019-06-27 Peter Cudmore , Peter J. Gawthrop , Michael Pan , Edmund J. Crampin
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