All the numerical examples of convolutions that I have seen thus far always assume that the input image has only 1 channel (for example, see this post on stack overflow). This made me wonder how the computations would work when the input image has multiple channels. I created this Sage worksheet to help me follow the computations.
I was reading this post about using 1D convolution on stack overflow and wondered how it would 1D work when the input has more than 1 channel and/or the output channel of the kernel is greater than one. So, I made this Sage Worksheet to see how the 1D convolution of a 2-channel 1-dimensional input vector with where the output channel of the kernel is 4 could be done by hand.
I made a document that goes through some calculations to show the effect of estimating probabilities using the maximum entropy method. It has code in it so that the reader can understand how the numbers were derived. Click here to download the pdf document. All computations were done using SageMath.
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