Search Results for "edmonds-karp algorithm implementation in python"

Showing 8 open source projects for "edmonds-karp algorithm implementation in python"

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  • 1
    nghttp2

    nghttp2

    HTTP/2 C Library and tools

    nghttp2 is an implementation of HTTP/2 and its header compression algorithm HPACK in C. The framing layer of HTTP/2 is implemented as a form of reusable C library. On top of that, we have implemented HTTP/2 client, server and proxy. We have also developed a load test and benchmarking tool for HTTP/2. We have participated in httpbis working group since HTTP/2 draft-04, which is the first implementation draft.
    Downloads: 3 This Week
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  • 2
    Imagen - Pytorch

    Imagen - Pytorch

    Implementation of Imagen, Google's Text-to-Image Neural Network

    Implementation of Imagen, Google's Text-to-Image Neural Network that beats DALL-E2, in Pytorch. It is the new SOTA for text-to-image synthesis. Architecturally, it is actually much simpler than DALL-E2. It consists of a cascading DDPM conditioned on text embeddings from a large pre-trained T5 model (attention network). It also contains dynamic clipping for improved classifier-free guidance, noise level conditioning, and a memory-efficient unit design. It appears neither CLIP nor prior...
    Downloads: 5 This Week
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  • 3
    AlphaZero.jl

    AlphaZero.jl

    A generic, simple and fast implementation of Deepmind's AlphaZero

    Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++)...
    Downloads: 21 This Week
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  • 4
    AES Everywhere

    AES Everywhere

    Cross Language AES 256 Encryption Library

    AES Everywhere is Cross Language Encryption Library that provides the ability to encrypt and decrypt data using a single algorithm in different programming languages and on different platforms. This is an implementation of the AES algorithm, specifically CBC mode, with 256-bit key length and PKCS7 padding. It implements OpenSSL-compatible cryptography with randomly generated salt.
    Downloads: 0 This Week
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  • 5
    node2vec

    node2vec

    Learn continuous vector embeddings for nodes in a graph using biased R

    The node2vec project provides an implementation of the node2vec algorithm, a scalable feature learning method for networks. The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction....
    Downloads: 12 This Week
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  • 6
    Gumbo

    Gumbo

    An HTML5 parsing library in pure C99

    Gumbo is an implementation of the HTML5 parsing algorithm implemented as a pure C99 library with no outside dependencies. It's designed to serve as a building block for other tools and libraries such as linters, validators, templating languages, and refactoring and analysis tools. Gumbo gains some of this by virtue of being written in C, but it is not an important consideration for the intended use-case, and was not a major design factor.
    Downloads: 0 This Week
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  • 7
    Fast cython implementation of trie data structure for Python. Development is inactive, but moved to: http://github.com/martinkozak/cytrie.
    Downloads: 0 This Week
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  • 8
    CRFasRNN

    CRFasRNN

    Semantic image segmentation method described in the ICCV 2015 paper

    CRF-RNN is a deep neural architecture that integrates fully connected Conditional Random Fields (CRFs) with Convolutional Neural Networks (CNNs) by reformulating mean-field CRF inference as a Recurrent Neural Network. This fusion enables end-to-end training via backpropagation for semantic image segmentation tasks, eliminating the need for separate, offline post-processing steps. Our work allows computers to recognize objects in images, what is distinctive about our work is that we also...
    Downloads: 0 This Week
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