Showing 11 open source projects for "publication"

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  • 1
    Matplotlib

    Matplotlib

    matplotlib: plotting with Python

    Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Matplotlib ships with several add-on toolkits, including 3D plotting with mplot3d, axes helpers in axes_grid1 and axis helpers in axisartist. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a...
    Downloads: 18 This Week
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  • 2
    plotly.py

    plotly.py

    The interactive graphing library for Python

    plotly.py is a browser-based, open source graphing library for Python that lets you create beautiful, interactive, publication-quality graphs. Built on top of plotly.js, it is a high-level, declarative charting library that ships with more than 30 chart types. Everything from statistical charts and scientific charts, through to maps, 3D graphs and animations, plotly.py lets you create them all. Graphs made with plotly.py can be viewed in Jupyter notebooks, standalone HTML files, or hosted online using Chart Studio Cloud.
    Downloads: 1 This Week
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  • 3
    Alphafold

    Alphafold

    Open source code for AlphaFold

    ...This is a completely new model that was entered in CASP14 and published in Nature. For simplicity, we refer to this model as AlphaFold throughout the rest of this document. Any publication that discloses findings arising from using this source code or the model parameters should cite the AlphaFold paper. Please also refer to the Supplementary Information for a detailed description of the method. You can use a slightly simplified version of AlphaFold with this Colab notebook or community-supported versions. The total download size for the full databases is around 415 GB and the total size when unzipped is 2.2 TB. ...
    Downloads: 5 This Week
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  • 4
    AlphaTensor

    AlphaTensor

    AI discovers faster, efficient algorithms for matrix multiplication

    AlphaTensor, developed by Google DeepMind, is the research codebase accompanying the 2022 Nature publication “Discovering faster matrix multiplication algorithms with reinforcement learning.” The project demonstrates how reinforcement learning can be used to automatically discover efficient algorithms for matrix multiplication — a fundamental operation in computer science and numerical computation. The repository is organized into four main components: algorithms, benchmarking, nonequivalence, and recombination. ...
    Downloads: 3 This Week
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  • 5
    Legit

    Legit

    Git for Humans, Inspired by GitHub for Mac™

    Legit is a complementary command-line interface for Git, optimized for workflow simplicity. It is heavily inspired by GitHub for Mac. We haven't re-created the git CLI tool in a GUI, we've created something different. We've created a tool that makes Git more accessible. Little things like auto-stashing when you switch branches will confuse git veterans, but it will make Git much easier to grok for newcomers because of the assumptions it makes about your Git workflow. Switches to specified...
    Downloads: 0 This Week
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  • 6

    etalon

    Standards Document Redaction System

    The best process for creating standards is that of the IETF’s RFCs. Standard documents are written, submitted for publication, reviewed, and finally approved. Then they get a official number and hence can be referenced. Some can even be blessed to be an official standard. Etalon will implement this whole process, web-based and with markdown documents. Create your company’s standards the RFC way!
    Downloads: 0 This Week
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  • 7
    Mixup-CIFAR10

    Mixup-CIFAR10

    mixup: Beyond Empirical Risk Minimization

    mixup-cifar10 is the official PyTorch implementation of “mixup: Beyond Empirical Risk Minimization” (Zhang et al., ICLR 2018), a foundational paper introducing mixup, a simple yet powerful data augmentation technique for training deep neural networks. The core idea of mixup is to generate synthetic training examples by taking convex combinations of pairs of input samples and their labels. By interpolating both data and labels, the model learns smoother decision boundaries and becomes more...
    Downloads: 0 This Week
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  • 8
    matplotlib
    Matplotlib is a python library for making publication quality plots using a syntax familiar to MATLAB users. Matplotlib uses numpy for numerics. Output formats include PDF, Postscript, SVG, and PNG, as well as screen display. As of matplotlib version 1.5, we are no longer making file releases available on SourceForge. Please visit http://matplotlib.org/users/installing.html for help obtaining matplotlib.
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    Downloads: 89 This Week
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  • 9

    ProximityForest

    Efficient Approximate Nearest Neighbors for General Metric Spaces

    ...See: O'Hara and Draper, "Are You Using the Right Approximate Nearest Neighbor Algorithm?", WACV 2013 (best student paper award). One application of a ProximityForest is given in the following CVPR publication: Stephen O'Hara and Bruce A. Draper, "Scalable Action Recognition with a Subspace Forest," IEEE Conference on Computer Vision and Pattern Recognition, 2012. This source code is provided without warranty and is available under the GPL license. More commercially-friendly licenses may be available. Please contact Stephen O'Hara for license options. ...
    Downloads: 0 This Week
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  • 10

    REST in Py

    Rest-in-py project has been moved to BitBucket

    Rest-in-py project has been moved to BitBucket https://bitbucket.org/fundacionctic/rest-in-py REST in PY ia a Python library to ease the publication of REST-style web services in Django applications, specially (but not exclusively) those using the Django Model framework.
    Downloads: 0 This Week
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  • 11
    PONY - ORM & web publication framework

    PONY - ORM & web publication framework

    Pony is a fast and easy to use Python ORM

    Pony is an object-relational mapper. The most interesting feature of Pony is its ability to write queries to the database using generator expressions. Pony works with entities which are mapped to a SQL database. Using generator syntax for writing queries allows the user to formulate very eloquent queries. It increases the level of abstraction and allows a programmer to concentrate on the business logic of the application. Following is an example of a query in Pony: select(p for p in...
    Downloads: 0 This Week
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