How many parameters does the neural network have?
2019年8月26日 · We have a neural network with an input layer of ℎ0 nodes, hidden layers of ℎ1 , ℎ2 , ℎ3 , ..., ℎ푙−1 nodes respectively and an output layer of ℎ푙 nodes. How many parameters does the network
convolutional codes: free distance - Mathematics Stack Exchange
2023年9月8日 · In the context of convolutional codes, the smallest Hamming distance between any two valid codewords is called the free distance. Specifically, the free distance of a convolutional code is the difference in path metrics between the all-zeroes output and the path with the smallest non-zero path metric going from the initial $00$ state to some ...
Can every piecewise linear function be exactly realized as a neural ...
2021年6月15日 · The main idea of that paper is that it is easy to build first-order finite elements by ReLU nets. You can therefore build everything that is a sum of linear finite elements also as a ReLU neural network. This includes all continuous piecewise affine functions (Theorem 5.2 of the linked paper.) $\endgroup$ –
Intuitive explanation of the backward Kolmogorov equation?
2024年10月9日 · In modern applications, it turns out that score functions can be effectively trained using deep neural networks, and many state-of-the-art image/video generation models are based on this idea. $\endgroup$
Derivative of Softmax loss function - Mathematics Stack Exchange
$\begingroup$ For others who end up here, this thread is about computing the derivative of the cross-entropy function, which is the cost function often used with a softmax layer (though the derivative of the cross-entropy function uses the derivative of the softmax, -p_k * y_k, in the equation above).
Show that convolution of two measurable functions is well-defined
Stack Exchange Network. Stack Exchange network consists of 183 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. Visit Stack Exchange
probability - Derivation of Bethe free energy in the context of ...
2009年2月2日 · Stack Exchange Network. Stack Exchange network consists of 183 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. Visit Stack Exchange
The Langlands program for beginners - Mathematics Stack Exchange
Stack Exchange Network. Stack Exchange network consists of 183 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. Visit Stack Exchange
matrices - Using Chain Rule in Matrix Differentiation
2017年11月12日 · Rather than the chain rule, let's tackle the problem using differentials. Let's use the convention that an upppercase letter is a matrix, lowercase is a column vector, and a greek letter is a scalar.
Derivative of Binary Cross Entropy - why are my signs not right?
2017年11月4日 · I'm trying to derive formulas used in backpropagation for a neural network that uses a binary cross entropy loss function. When I perform the differentiation, however, my signs do not come out rig...