Showing 8 open source projects for "backpropagation network"

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  • 1
    Hivemind

    Hivemind

    Decentralized deep learning in PyTorch. Built to train models

    ...Its intended usage is training one large model on hundreds of computers from different universities, companies, and volunteers. Distributed training without a master node: Distributed Hash Table allows connecting computers in a decentralized network. Fault-tolerant backpropagation: forward and backward passes succeed even if some nodes are unresponsive or take too long to respond. Decentralized parameter averaging: iteratively aggregate updates from multiple workers without the need to synchronize across the entire network. Train neural networks of arbitrary size: parts of their layers are distributed across the participants with the Decentralized Mixture-of-Experts. ...
    Downloads: 4 This Week
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  • 2
    DeepLearning Tutorial

    DeepLearning Tutorial

    Deep Learning Tutorial, Excellent Articles, Deep Learning Tutorial

    DeepLearning is an open-source repository that aggregates tutorials, articles, and educational resources related to deep learning and machine learning. The project is designed as a knowledge collection that helps beginners understand neural networks, deep learning architectures, and fundamental machine learning concepts. It contains curated learning materials covering topics such as feedforward neural networks, activation functions, backpropagation algorithms, optimization methods, and...
    Downloads: 0 This Week
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  • 3
    Keras TCN

    Keras TCN

    Keras Temporal Convolutional Network

    TCNs exhibit longer memory than recurrent architectures with the same capacity. Performs better than LSTM/GRU on a vast range of tasks (Seq. MNIST, Adding Problem, Copy Memory, Word-level PTB...). Parallelism (convolutional layers), flexible receptive field size (possible to specify how far the model can see), stable gradients (backpropagation through time, vanishing gradients). The usual way is to import the TCN layer and use it inside a Keras model. The receptive field is defined as the...
    Downloads: 0 This Week
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  • 4
    Java Neural Network Framework Neuroph
    Neuroph is lightweight Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and GUI editor makes it easy to learn and use.
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    Downloads: 214 This Week
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  • 5
    LensOSX

    LensOSX

    LensOSX: the light, efficient network simulator

    Lens is the light, efficient network simulator, written by Doug Rohde. LensOSX is a native MacOSX port of Lens that runs on MacOSX 10.5 or higher, created by Harm Brouwer, Daniel de Kok and Hartmut Fitz.
    Downloads: 0 This Week
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  • 6
    OSXtlearn

    OSXtlearn

    OSXtlearn: tlearn for MacOSX

    tlearn is a backpropagation neural network simulator, written by Jeff Elman. xtlearn is a version of tlearn for the X Window System. OSXtlearn is xtlearn wrapped in a MacOSX application bundle that runs ons MacOSX 10.5 or higher and that requires XQuartz. OSXtlearn is created by Harm Brouwer.
    Downloads: 2 This Week
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  • 7

    cognity

    A neural network library for Java.

    Cognity is an object-oriented neural network library for Java. It's goal is to provide easy-to-use, high level architecture for neural network computations along with reasonable performance.
    Downloads: 0 This Week
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  • 8
    Nen

    Nen

    neural network implementation in java

    3-layer neural network for regression and classification with sigmoid activation function and command line interface similar to LibSVM. Quick Start: "java -jar nen.jar"
    Downloads: 0 This Week
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