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  2. Residual neural network - Wikipedia

    en.wikipedia.org/wiki/Residual_neural_network

    Examples include: [17] [18] Lang and Witbrock (1988) [19] trained a fully connected feedforward network where each layer skip-connects to all subsequent layers, like the later DenseNet (2016). In this work, the residual connection was the form x ↦ F ( x ) + P ( x ) {\displaystyle x\mapsto F(x)+P(x)} , where P {\displaystyle P} is a randomly ...

  3. Project Euler - Wikipedia

    en.wikipedia.org/wiki/Project_Euler

    Project Euler (named after Leonhard Euler) is a website dedicated to a series of computational problems intended to be solved with computer programs. [ 1 ] [ 2 ] The project attracts graduates and students interested in mathematics and computer programming .

  4. Comparison of BitTorrent clients - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_BitTorrent...

    The following is a general comparison of BitTorrent clients, which are computer programs designed for peer-to-peer file sharing using the BitTorrent protocol. [1]The BitTorrent protocol coordinates segmented file transfer among peers connected in a swarm.

  5. Torrent Project - Wikipedia

    en.wikipedia.org/wiki/Torrent_Project

    The Torrent Project or Torrent Search Project was a metasearch engine for torrent files, which consolidated links from other popular torrent hosting pages such as ExtraTorrent. [1] It was available as an alternative and successor for the closed Torrentz.eu and KickassTorrents sites, [ 2 ] and its index included over 8 million torrent files, and ...

  6. Bencode - Wikipedia

    en.wikipedia.org/wiki/Bencode

    Examples: Zero is encoded as i0e. The number 42 is encoded as i42e. Negative forty-two is encoded as i-42e. Byte Strings are encoded as <length>:<contents>. The length is the number of bytes in the string, encoded in base 10. A colon (:) separates the length and the contents. The contents are the exact number of bytes specified by the length ...

  7. Vanishing gradient problem - Wikipedia

    en.wikipedia.org/wiki/Vanishing_gradient_problem

    The product of repeated multiplication with such gradients decreases exponentially. The inverse problem, when weight gradients at earlier layers get exponentially larger, is called the exploding gradient problem. Backpropagation allowed researchers to train supervised deep artificial neural networks from scratch, initially with little success.

  8. File:Resnet-18 architecture.svg - Wikipedia

    en.wikipedia.org/wiki/File:Resnet-18...

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  9. AlexNet - Wikipedia

    en.wikipedia.org/wiki/AlexNet

    The next convolution should be 11×11 with stride 4: 55×55×96 (instead of 54×54×96). It would be calculated, for example, as: [(input width 227 - kernel width 11) / stride 4] + 1 = [(227 - 11) / 4] + 1 = 55. Since the kernel output is the same length as width, its area is 55×55.) AlexNet is a convolutional neural network.