Showing 5 open source projects for "graph visualization"

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  • 1
    Materials Discovery: GNoME

    Materials Discovery: GNoME

    AI discovers 520000 stable inorganic crystal structures for research

    Materials Discovery (GNoME) is a large-scale research initiative by Google DeepMind focused on applying graph neural networks to accelerate the discovery of stable inorganic crystal materials. The project centers on Graph Networks for Materials Exploration (GNoME), a message-passing neural network architecture trained on density functional theory (DFT) data to predict material stability and energy formation. Using GNoME, DeepMind identified 381,000 new stable materials, later expanding the...
    Downloads: 3 This Week
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  • 2
    Apache Hamilton

    Apache Hamilton

    Helps data scientists define testable self-documenting dataflows

    Apache Hamilton is an open-source Python framework designed to simplify the creation and management of dataflows used in analytics, machine learning pipelines, and data engineering workflows. The framework enables developers to define data transformations as simple Python functions, where each function represents a node in a dataflow graph and its parameters define dependencies on other nodes. Hamilton automatically analyzes these functions and constructs a directed acyclic graph...
    Downloads: 0 This Week
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  • 3
    Pattern

    Pattern

    Web mining module for Python, with tools for scraping

    Pattern is an open-source Python library that provides tools for web mining, natural language processing, machine learning, and network analysis. The project integrates multiple capabilities into a single framework that allows developers to collect, process, and analyze textual data from the web. It includes modules for web scraping and crawling that can retrieve information from sources such as social media platforms, search engines, and online knowledge bases. In addition to data mining...
    Downloads: 0 This Week
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  • 4
    TFLearn

    TFLearn

    Deep learning library featuring a higher-level API for TensorFlow

    ...Full transparency over Tensorflow. All functions are built over tensors and can be used independently of TFLearn. Powerful helper functions to train any TensorFlow graph, with support of multiple inputs, outputs, and optimizers. Easy and beautiful graph visualization, with details about weights, gradients, activations, and more. Effortless device placement for using multiple CPU/GPU. The high-level API currently supports the most of the recent deep learning models, such as Convolutions, LSTM, BiRNN, BatchNorm, etc.
    Downloads: 0 This Week
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  • 5
    StellarGraph

    StellarGraph

    Machine Learning on Graphs

    StellarGraph is a Python library for machine learning on graphs and networks. The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks. Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can...
    Downloads: 0 This Week
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