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  2. Rectifier (neural networks) - Wikipedia

    en.wikipedia.org/wiki/Rectifier_(neural_networks)

    Plot of the ReLU (blue) and GELU (green) functions near x = 0. In the context of artificial neural networks, the rectifier or ReLU (rectified linear unit) activation function [1] [2] is an activation function defined as the non-negative part of its argument, i.e., the ramp function:

  3. Activation function - Wikipedia

    en.wikipedia.org/wiki/Activation_function

    The activation function of a node in an artificial neural network is a function that calculates the output of the node based on its individual inputs and their weights. Nontrivial problems can be solved using only a few nodes if the activation function is nonlinear .

  4. Swish function - Wikipedia

    en.wikipedia.org/wiki/Swish_function

    The swish paper was then updated to propose the activation with the learnable parameter β. In 2017, after performing analysis on ImageNet data, researchers from Google indicated that using this function as an activation function in artificial neural networks improves the performance, compared to ReLU and sigmoid functions. [1]

  5. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    PyTorch is a machine learning library based on the Torch library, [4] [5] [6] ... ReLU (), # ReLU is one of many activation functions provided by nn nn.

  6. Ramp function - Wikipedia

    en.wikipedia.org/wiki/Ramp_function

    In mathematics, the ramp function is also known as the positive part. In machine learning, it is commonly known as a ReLU activation function [1] [2] or a rectifier in analogy to half-wave rectification in electrical engineering. In statistics (when used as a likelihood function) it is known as a tobit model.

  7. Feedforward neural network - Wikipedia

    en.wikipedia.org/wiki/Feedforward_neural_network

    Alternative activation functions have been proposed, including the rectifier and softplus functions. More specialized activation functions include radial basis functions (used in radial basis networks, another class of supervised neural network models). In recent developments of deep learning the rectified linear unit (ReLU) is more frequently ...

  8. Universal approximation theorem - Wikipedia

    en.wikipedia.org/wiki/Universal_approximation...

    This is an existence result. It says that activation functions providing universal approximation property for bounded depth bounded width networks exist. Using certain algorithmic and computer programming techniques, Guliyev and Ismailov efficiently constructed such activation functions depending on a numerical parameter.

  9. RLU - Wikipedia

    en.wikipedia.org/wiki/RLU

    Rectified linear unit, a neuron activation function used in neural networks, usually referred to as an ReLU; Relative light unit, a unit for measuring cleanliness by measuring the levels of Adenosine Triphosphate; Remote line unit, a type of switch in the GTD-5 EAX switching system; RLU-1 Breezy, an American homebuilt aircraft design