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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. Leela Zero - Wikipedia

    en.wikipedia.org/wiki/Leela_Zero

    The body is a ResNet with 40 residual blocks and 256 channels. There are two heads, a policy head and a value head. Policy head outputs a logit array of size 19 × 19 + 1 {\displaystyle 19\times 19+1} , representing the logit of making a move in one of the points, plus the logit of passing .

  4. AlphaGo Zero - Wikipedia

    en.wikipedia.org/wiki/AlphaGo_Zero

    The body is a ResNet with either 20 or 40 residual blocks and 256 channels. There are two heads, a policy head and a value head. Policy head outputs a logit array of size 19 × 19 + 1 {\displaystyle 19\times 19+1} , representing the logit of making a move in one of the points, plus the logit of passing .

  5. Kaiming He - Wikipedia

    en.wikipedia.org/wiki/Kaiming_He

    He is an associate professor at Massachusetts Institute of Technology and is known as one of the creators of residual neural network (ResNet). [ 1 ] [ 3 ] Early life and education

  6. Universal approximation theorem - Wikipedia

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

    For the algorithm and the corresponding computer code see. [14] The theoretical result can be formulated as follows. Universal approximation theorem: [ 14 ] [ 15 ] — Let [ a , b ] {\displaystyle [a,b]} be a finite segment of the real line, s = b − a {\displaystyle s=b-a} and λ {\displaystyle \lambda } be any positive number.

  7. Activation function - Wikipedia

    en.wikipedia.org/wiki/Activation_function

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

  8. World juniors USA vs. Finland: How to watch hockey gold-medal ...

    www.aol.com/world-juniors-usa-vs-finland...

    Sweden and Czechia will play for bronze at 3:30. How to watch USA vs. Finland world juniors hockey game Both games will be shown on NHL Network in the United States and on TSN in Canada.

  9. AlexNet - Wikipedia

    en.wikipedia.org/wiki/AlexNet

    AlexNet block diagram AlexNet is a convolutional neural network (CNN) architecture, designed by Alex Krizhevsky in collaboration with Ilya Sutskever and Geoffrey Hinton , who was Krizhevsky's Ph.D. advisor at the University of Toronto in 2012.