Showing 5 open source projects for "graph isomorphism algorithm"

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  • 1
    Spektral

    Spektral

    Graph Neural Networks with Keras and Tensorflow 2

    Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to provide a simple but flexible framework for creating graph neural networks (GNNs). You can use Spektral for classifying the users of a social network, predicting molecular properties, generating new graphs with GANs, clustering nodes, predicting links, and any other task where data is described by graphs. Spektral implements some of the most popular layers for...
    Downloads: 0 This Week
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  • 2
    MACE

    MACE

    Deep learning inference framework optimized for mobile platforms

    Graph level memory allocation optimization and buffer reuse are supported. The core library tries to keep minimum external dependencies to keep the library footprint small.
    Downloads: 0 This Week
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  • 3
    Easy Machine Learning

    Easy Machine Learning

    Easy Machine Learning is a general-purpose dataflow-based system

    ...Our platform Easy Machine Learning presents a general-purpose dataflow-based system for easing the process of applying machine learning algorithms to real-world tasks. In the system, a learning task is formulated as a directed acyclic graph (DAG) in which each node represents an operation (e.g. a machine learning algorithm), and each edge represents the flow of the data from one node to its descendants.
    Downloads: 0 This Week
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  • 4
    This project aims to develop and share fast frequent subgraph mining and graph learning algorithms. Currently we release the frequent subgraph mining package FFSM and later we will include new functions for graph regression and classification package
    Downloads: 0 This Week
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  • 5
    BorderFlow
    BorderFlow implements a general-purpose graph clustering algorithm. It maximizes the inner to outer flow ratio from the border of each cluster to the rest of the graph.
    Downloads: 0 This Week
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