Showing 2 open source projects for "edmonds-karp algorithm implementation in python"

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    Bayesian Optimization

    Bayesian Optimization

    Python implementation of global optimization with gaussian processes

    This is a constrained global optimization package built upon bayesian inference and gaussian process, that attempts to find the maximum value of an unknown function in as few iterations as possible. This technique is particularly suited for optimization of high cost functions, situations where the balance between exploration and exploitation is important. More detailed information, other advanced features, and tips on usage/implementation can be found in the examples folder. Follow the basic...
    Downloads: 2 This Week
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    TSNE-CUDA

    TSNE-CUDA

    GPU Accelerated t-SNE for CUDA with Python bindings

    This repo is an optimized CUDA version of FIt-SNE algorithm with associated python modules. We find that our implementation of t-SNE can be up to 1200x faster than Sklearn, or up to 50x faster than Multicore-TSNE when used with the right GPU. You can install binaries with anaconda for CUDA version 10.1 and 10.2 using conda install tsnecuda -c conda-forge. Tsnecuda supports CUDA versions 9.0 and later through source installation, check out the wiki for up to date installation instructions. Time...
    Downloads: 1 This Week
    Last Update:
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