Questions tagged [deconvolution]
6 questions
7
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Distribution of i.i.d. random variables $X$ and $Y$ if $XY \sim \text{Beta}(\alpha, \beta)$
This is a follow-up to the question Square root of a Beta(1,1) random variable, which received two great answers.
If $XY \sim \text{Beta}(\alpha, \beta)$, and $X$ and $Y$ are two independent identically distributed random variables, do we know their…
LuckyPal
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Cellular deconvolution intuition
Cellular deconvolution yields the proportion of cell types from bulk tissue.
After estimating the proportion of each cell type, why cannot one multiply the total expression by the proportion to get the expression by cell type?
Unsupervised…
Sam
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Estimate the Image Using Multi Many Realizations of Its Convolution with a Known Filters Using Wiener Filter
Suppose we have a corrupted image $Y = H*X + \epsilon$ that is formed by taking an image $X$, convolving it with a point-spread function $H$, and adding gaussian noise $\epsilon$. Then we know that the Wiener Filter can compute the MMSE estimator of…
Sunay Joshi
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Deconvolution of mixed signals from tumor data
I have N tumor-normal sample pairs from the same tissue of N subjects. For each sample, I have expression measurements for a fixed gene panel (M genes).
The tumors are additionally also contaminated with normals. Therefore, the measurements in…
Stats_sc
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Recovering weights between neurons in a convolutional layer
Given a convolutional layer, I am interested in recovering the weight matrix $W$, where $w_{i,j}$ is the weight between neuron $i$ in the input layer and neuron $j$ in the output layer. I know that most of these will be zero (e.g. for a 3x3 kernel…
Josh Bone
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Dilated deconvolutions
Can anybody please outline some use cases for dilated deconvolution?
In the literature, one can find lots of references about dilated convolutions, but nothing about dilated deconvolution? Does it make sense to use them? In libraries like Tensorflow…
rick87
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