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  2. Residual neural network - Wikipedia

    en.wikipedia.org/wiki/Residual_neural_network

    A basic block is the simplest building block studied in the original ResNet. [1] This block consists of two sequential 3x3 convolutional layers and a residual connection. The input and output dimensions of both layers are equal. Block diagram of ResNet (2015). It shows a ResNet block with and without the 1x1 convolution.

  3. Inception (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Inception_(deep_learning...

    As an example, a single 5×5 convolution can be factored into 3×3 stacked on top of another 3×3. Both has a receptive field of size 5×5. The 5×5 convolution kernel has 25 parameters, compared to just 18 in the factorized version. Thus, the 5×5 convolution is strictly more powerful than the factorized version.

  4. Vanishing gradient problem - Wikipedia

    en.wikipedia.org/wiki/Vanishing_gradient_problem

    Residual connections, or skip connections, refers to the architectural motif of +, where is an arbitrary neural network module. This gives the gradient of ∇ f + I {\displaystyle \nabla f+I} , where the identity matrix do not suffer from the vanishing or exploding gradient.

  5. Activation function - Wikipedia

    en.wikipedia.org/wiki/Activation_function

    Modern activation functions include the logistic function used in the 2012 speech recognition model developed by Hinton et al; [2] the ReLU used in the 2012 AlexNet computer vision model [3] [4] and in the 2015 ResNet model; and the smooth version of the ReLU, the GELU, which was used in the 2018 BERT model. [5]

  6. File:ResNet block.svg - Wikipedia

    en.wikipedia.org/wiki/File:ResNet_block.svg

    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.

  7. Minimal residual method - Wikipedia

    en.wikipedia.org/wiki/Minimal_residual_method

    Both minimize the 2-norm of the residual and do the same calculations in exact arithmetic when the matrix is symmetric. MINRES is a short-recurrence method with a constant memory requirement, whereas GMRES requires storing the whole Krylov space, so its memory requirement is roughly proportional to the number of iterations.

  8. Johnson & Johnson (JNJ) Q4 2024 Earnings Call Transcript - AOL

    www.aol.com/finance/johnson-johnson-jnj-q4-2024...

    We anticipate operational sales in the range of 2.5% to 3.5%, with a midpoint of $91.3 billion or 3%, in line with the expectation outlined at our late 2023 Enterprise Business Review, as Joaquin ...

  9. Process control block - Wikipedia

    en.wikipedia.org/wiki/Process_control_block

    A process control block (PCB), also sometimes called a process descriptor, is a data structure used by a computer operating system to store all the information about a process. When a process is created (initialized or installed), the operating system creates a corresponding process control block, which specifies and tracks the process state (i ...