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Meng's Notes

Friday, September 11, 2015. I found this paper. Http:/ arxiv.org/pdf/1508.06576v2.pdf. Very clear and well-written. People quickly released its implementation such as https:/ github.com/kaishengtai/neuralart. The major contribution of the paper seems to be the content/style decomposition of an image (as described in Equation 1, 5 and 7). The style representation (equation 4) seems to be the key. Potential applications of this paper's idea could be interesting too. Such as to make camouflage given env...

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Friday, September 11, 2015. I found this paper. Http:/ arxiv.org/pdf/1508.06576v2.pdf. Very clear and well-written. People quickly released its implementation such as https:/ github.com/kaishengtai/neuralart. The major contribution of the paper seems to be the content/style decomposition of an image (as described in Equation 1, 5 and 7). The style representation (equation 4) seems to be the key. Potential applications of this paper's idea could be interesting too. Such as to make camouflage given env...

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Meng's Notes | mengnote.blogspot.com Reviews

https://mengnote.blogspot.com

Friday, September 11, 2015. I found this paper. Http:/ arxiv.org/pdf/1508.06576v2.pdf. Very clear and well-written. People quickly released its implementation such as https:/ github.com/kaishengtai/neuralart. The major contribution of the paper seems to be the content/style decomposition of an image (as described in Equation 1, 5 and 7). The style representation (equation 4) seems to be the key. Potential applications of this paper's idea could be interesting too. Such as to make camouflage given env...

INTERNAL PAGES

mengnote.blogspot.com

1

Meng's Notes: Style = Correlation?

http://www.mengnote.blogspot.com/2015/09/style-correlation.html

Friday, September 11, 2015. I found this paper. Http:/ arxiv.org/pdf/1508.06576v2.pdf. Very clear and well-written. People quickly released its implementation such as https:/ github.com/kaishengtai/neuralart. The major contribution of the paper seems to be the content/style decomposition of an image (as described in Equation 1, 5 and 7). The style representation (equation 4) seems to be the key. Potential applications of this paper's idea could be interesting too. Such as to make camouflage given env...

2

Meng's Notes: How much confidence can we obtain from a piece of evidence?

http://www.mengnote.blogspot.com/2013/03/how-much-confidence-can-we-obtain-from.html

Tuesday, March 19, 2013. How much confidence can we obtain from a piece of evidence? Every one knows that most computational predictions on biological systems are "less confidential" although many methods were based on convincible evidences and were announced of having high accuracy. But why these theoretically applicable methods failed to give reliable outputs? Frac{chance of people having cancer, given an evidence (positive test)}{chance of people having cancer, in general (given no special evidence)}$...

3

Meng's Notes: September 2015

http://www.mengnote.blogspot.com/2015_09_01_archive.html

Friday, September 11, 2015. I found this paper. Http:/ arxiv.org/pdf/1508.06576v2.pdf. Very clear and well-written. People quickly released its implementation such as https:/ github.com/kaishengtai/neuralart. The major contribution of the paper seems to be the content/style decomposition of an image (as described in Equation 1, 5 and 7). The style representation (equation 4) seems to be the key. Potential applications of this paper's idea could be interesting too. Such as to make camouflage given env...

4

Meng's Notes: Simple Enrichment Test -- calculate hypergeometric p-values in R

http://www.mengnote.blogspot.com/2012/12/calculate-correct-hypergeometric-p.html

Wednesday, December 19, 2012. Simple Enrichment Test - calculate hypergeometric p-values in R. Hypergeometric test are useful for enrichment analysis. For example, having a gene list in hand, people might want to tell which functions (GO terms) are enriched among these genes. Hypergeometric test (or its equivalent: one-tailed Fisher's exact test) will give you statistical confidence in (p )-values. R software provids function phyper. Here is a simple example:. The number of diamonds selected. Could be 0 5.

5

Meng's Notes: May 2013

http://www.mengnote.blogspot.com/2013_05_01_archive.html

Wednesday, May 8, 2013. An intuitive explanation of PCA (Principal Component Analysis). For a mathematical method, I believe most people only need to understand the logic and limitations of it and let software packages to do the rest (implementation, calculation, etc.). Here I am trying to explain that PCA is not an impenetrable soup of acronyms but a quite intuitive approach. It can make large-scale data smaller and easier to handle. Subscribe to: Posts (Atom). View my complete profile.

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mengnote.blogspot.com

Meng's Notes

Friday, September 11, 2015. I found this paper. Http:/ arxiv.org/pdf/1508.06576v2.pdf. Very clear and well-written. People quickly released its implementation such as https:/ github.com/kaishengtai/neuralart. The major contribution of the paper seems to be the content/style decomposition of an image (as described in Equation 1, 5 and 7). The style representation (equation 4) seems to be the key. Potential applications of this paper's idea could be interesting too. Such as to make camouflage given env...

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