Showing 21 open source projects for "algorithms framework"

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  • 1
    Perceval

    Perceval

    An open source framework for programming photonic quantum computers

    An open-source framework for programming photonic quantum computers. Through a simple object-oriented Python API, Perceval provides tools for composing circuits from linear optical components, defining single-photon sources, manipulating Fock states, running simulations, reproducing published experimental papers and experimenting with a new generation of quantum algorithms.
    Downloads: 2 This Week
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  • 2
    Tequila

    Tequila

    A High-Level Abstraction Framework for Quantum Algorithms

    Tequila is an abstraction framework for (variational) quantum algorithms. It operates on abstract data structures allowing the formulation, combination, automatic differentiation and optimization of generalized objectives. Tequila can execute the underlying quantum expectation values on state-of-the-art simulators as well as on real quantum devices.
    Downloads: 1 This Week
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  • 3
    robosuite

    robosuite

    A Modular Simulation Framework and Benchmark for Robot Learning

    Robosuite is a modular and extensible simulation framework for robotic manipulation tasks, built on top of MuJoCo. Developed by the ARISE Initiative, Robosuite offers a set of standardized benchmarks and customizable environments designed to advance research in robotic manipulation, control, and imitation learning. It emphasizes realistic simulations and ease of use for both single-task and multi-task learning.
    Downloads: 0 This Week
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  • 4

    jif3d

    3D Joint Inversion Framework

    jif3d is a framework for joint inversion of different types of geophysical data in 3D. It currently comprises forward solvers for first arrival traveltimes, scalar and tensor gravity data, magnetics, magnetotellurics, electrical resistivity tomography and surface waves.The framework is flexible in terms of the coupling approach between the different datasets. At the moment cross-gradient coupling, variation of information and deterministic parameter relationships are implemented. Other...
    Downloads: 5 This Week
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  • 5
    SMILI

    SMILI

    Scientific Visualisation Made Easy

    ...The main sMILX application features for viewing n-D images, vector images, DICOMs, anonymizing, shape analysis and models/surfaces with easy drag and drop functions. It also features a number of standard processing algorithms for smoothing, thresholding, masking etc. images and models, both with graphical user interfaces and/or via the command-line. See our YouTube channel for tutorial videos via the homepage. The applications are all built out of a uniform user-interface framework that provides a very high level (Qt) interface to powerful image processing and scientific visualisation algorithms from the Insight Toolkit (ITK) and Visualisation Toolkit (VTK). ...
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    Downloads: 10 This Week
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  • 6
    An open source framework for LC-MS based proteomics and metabolomics. OpenMS offers data structures and algorithms for the processing of mass spectrometry data. The library is written in C++. Our source code and wiki lives on GitHub (https://github.com/OpenMS/OpenMS).
    Downloads: 7 This Week
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  • 7
    plot.py

    plot.py

    direct data plotting and evaluation

    The Plot.py project tries to supply a measurement data visualization and treatment framework being easy to use while keeping the freedom for advanced users to execute additional data treatment algorithms. Plotting is done via gnuplot and the script used to produce the graphs can be exported for later use/changes. Many raw experimental data types (mostly of x-ray and neutron scattering experiments) are supported with more to be added on user request.
    Downloads: 0 This Week
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  • 8
    Phaistos
    Phaistos is a framework for all-atom Monte Carlo simulations of proteins. It incorporates several advanced probabilistic models of protein structure for conformational sampling, efficient move-algorithms and the OPLS and PROFASI forcefields.
    Downloads: 0 This Week
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  • 9
    Modular toolkit for Data Processing MDP
    The Modular toolkit for Data Processing (MDP) is a Python data processing framework. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures. From the scientific developer's perspective, MDP is a modular framework, which can easily be expanded.
    Downloads: 3 This Week
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  • 10
    scipion-xmipp

    scipion-xmipp

    Image processing framework to integrate EM software packages.

    ...Xmipp is a well-known package in the EM image processing. It is integrated into Scipion and contains the algorithms in the core libraries and command line programs.
    Downloads: 0 This Week
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  • 11

    fitGCP

    Fitting genome coverage distributions with mixture models

    ...fitGCP is a framework for fitting mixtures of probability distributions to genome coverage profiles. Besides commonly used distributions, fitGCP uses distributions tailored to account for common artifacts. The mixture models are iteratively fitted based on the Expectation-Maximization algorithm. Please find the accompanying paper here: http://dx.doi.org/10.1093/bioinformatics/btt147
    Downloads: 0 This Week
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  • 12
    JBoost is a simple, robust system for classification. JBoost contains implementations of several boosting algorithms in an alternating decision tree framework. In addition, JBoost provides extensible software for adding more learning algorithms.
    Downloads: 0 This Week
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  • 13
    Emulica emulation framework
    Emulica provides manufacturing control engineers and researchers with generic modeling components to build industry-scale virtual (emulated) shop floor systems, and thus test control approaches.
    Downloads: 0 This Week
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  • 14
    MIVF - Medical Imaging and Visualization Factory, is a framework for medical applications. It supplies a platform, in which image processing and 3D visualization algorithms can be employed as reusable components (functional modules or plugins).
    Downloads: 0 This Week
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  • 15
    PGAF provides a framework tuned, user-specific genetic algorithms by handling I/O, UI, and parallelism. It is designed for optimizing functions that take a "very long time" to evaluate.
    Downloads: 0 This Week
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  • 16
    The Automatic Model Optimization Reference Implementation, AMORI, is a framework that integrates the modelling and the optimization processes by providing a plug-in interface for both. A genetic algorithm and Markov simulations are currently implemented.
    Downloads: 0 This Week
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  • 17
    TAROT is a easy-to-use framework for Monte Carlo simulations in python. Calculations between different kinds of randomly distributed numbers are made as easy as basic arithmetics. Tarot provides an interactive graphical interface for interpretation.
    Downloads: 0 This Week
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  • 18
    pySPACE

    pySPACE

    Signal Processing and Classification Environment in Python using YAML

    pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. ...
    Downloads: 0 This Week
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  • 19
    ACF is a framework for writing model-checkers. ACF is built on the fundamental observation that the structure of most model-checking algorithms is independent of the formalism used to describe the system.
    Downloads: 0 This Week
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  • 20
    The LisBON Framework is an adaptable framework for developing new parallel Memetic Algorithms (hybrid search algorithms for efficiently solving optimisation problems).
    Downloads: 0 This Week
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  • 21
    ExoPlanet

    ExoPlanet

    GUI based toolkit for running common Machine Learning algorithms.

    ExoPlanet provides a graphical interface for the construction, evaluation and application of a Machine Learning model in predictive analysis. With the back-end built using the numpy and scikit-learn libraries, as a toolkit, ExoPlanet couples fast and well tested algorithms, a UI designed over the Qt4 framework, and graphs rendered using Matplotlib to provide the user with a rich interface, rapid analytics and interactive visuals. ExoPlanet is designed to have a minimal learning curve, allowing researchers to focus on the applicative aspect of Machine Learning rather than their implementation details. ...
    Downloads: 0 This Week
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