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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. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    In September 2022, Meta announced that PyTorch would be governed by the independent PyTorch Foundation, a newly created subsidiary of the Linux Foundation. [ 24 ] PyTorch 2.0 was released on 15 March 2023, introducing TorchDynamo , a Python-level compiler that makes code run up to 2x faster, along with significant improvements in training and ...

  4. Recurrent neural network - Wikipedia

    en.wikipedia.org/wiki/Recurrent_neural_network

    Recurrent neural networks (RNNs) are a class of artificial neural network commonly used for sequential data processing. Unlike feedforward neural networks, which process data in a single pass, RNNs process data across multiple time steps, making them well-adapted for modelling and processing text, speech, and time series.

  5. PyTorch Lightning - Wikipedia

    en.wikipedia.org/wiki/PyTorch_Lightning

    PyTorch Lightning is an open-source Python library that provides a high-level interface for PyTorch, a popular deep learning framework. [1] It is a lightweight and high-performance framework that organizes PyTorch code to decouple research from engineering, thus making deep learning experiments easier to read and reproduce.

  6. Open Neural Network Exchange - Wikipedia

    en.wikipedia.org/wiki/Open_Neural_Network_Exchange

    The Open Neural Network Exchange (ONNX) [ˈɒnɪks] [2] is an open-source artificial intelligence ecosystem [3] of technology companies and research organizations that establish open standards for representing machine learning algorithms and software tools to promote innovation and collaboration in the AI sector.

  7. Literate programming - Wikipedia

    en.wikipedia.org/wiki/Literate_programming

    Literate Programming by Donald Knuth is the seminal book on literate programming.. Literate programming is a programming paradigm introduced in 1984 by Donald Knuth in which a computer program is given as an explanation of how it works in a natural language, such as English, interspersed (embedded) with snippets of macros and traditional source code, from which compilable source code can be ...

  8. Subsidy Scorecards: Coppin State University

    projects.huffingtonpost.com/projects/ncaa/...

    SOURCE: Integrated Postsecondary Education Data System, Coppin State University (2014, 2013, 2012, 2011, 2010).Read our methodology here.. HuffPost and The Chronicle examined 201 public D-I schools from 2010-2014.

  9. Minimal reproducible example - Wikipedia

    en.wikipedia.org/wiki/Minimal_reproducible_example

    In computing, a minimal reproducible example (abbreviated MRE) [1] is a collection of source code and other data files which allow a bug or problem to be demonstrated and reproduced. The important feature of a minimal reproducible example is that it is as small and as simple as possible, such that it is just sufficient to demonstrate the ...