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Home Page: colah.github.io

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colah.github.io's Issues

Enable RSS feed auto-discovery

Hi! I noticed you have an RSS feed at https://colah.github.io/rss.xml, but it's not linked from anywhere. Please add the following to <head> of each page so that newsreaders could find the feed automatically:

<link rel="alternate" type="application/rss+xml" title="colah's blog" href="rss.xml">

Thank you.

Change Wording In ConvNet Post

First off, I would just like to say that your blog posts are awesome. The math you are blogging about is extremely complicated (if you are trying to read it via papers) but your posts definitely explain it in Layman's terms better than anything I have come across.

I would change the wording this paragraph from:

"At its most basic, convolutional neural networks can be thought of as a kind of neural network that uses many identical copies of the same neuron.1 This allows the network to have lots of neurons and express computationally large models while keeping the number of actual parameters – the values describing how neurons behave – that need to be learned fairly small."

to something like this

"At its most basic, convolutional neural networks can be thought of as a kind of neural network that uses many identical copies of the same neuron.1 This allows the network to have lots of neurons and express computationally large models while keeping the number of actual parameters (the values describing how neurons behave) that have to be learned fairly small."

I had to read that last sentence a few times to figure out what was going on. This makes more sense to me. Keep up the good work!

Blog Setup

Hello Mr. Olah,

I was going through your blog and really liked the design of the same. I was wondering if you are able to point me to how you set up the same - perhaps a website with instructions or if I can download your repo and try to recreate the same.

Thanks,
RJaikanth

Can I quote your picture about RNN in my paper？

https://camo.githubusercontent.com/90667bfb975db1e7ab28e6a176e722a9820205b2c3d0a912fae312b15477b46f/68747470733a2f2f636f6c61682e6769746875622e696f2f706f7374732f323031352d30382d556e6465727374616e64696e672d4c53544d732f696d672f4c53544d332d7661722d4752552e706e67
The picture you drawed is very fancy. can I use it to introduce RNN in my paper ? Thank you very much.

No automatic redirection from HTTP to HTTPS

colah.github.io has no automatic redirection from HTTP to HTTPS. It should, but until then, please make explicit calls to HTTPS.

What tool are you using for drawing recurrent neural network?

Hi, I think the lstm diagrams in your blog are fancy, may I ask what tool did you use to draw them?

hidden state not described in Understanding LSTMs

The hidden state is never described as part of LSTM, and is only mentioned in the section about GRU.
There is a paragraph that refers to both the cell state (C_t) and the hidden state (h_t) as "cell state". This is quite confusing, although the nearby graph provides some insight to what is really meant.

Wrong labels in LSTM diagram

In Understanding LSTM Networks blog the LSTM diagram has wrong labels this & this image. These are the correct labels:

Your figures are too good

Please can you tell me how you made your figures?! Particularly in this post and very specifically this image. Are you using Tikz or something manual?

Thank you for the great blogs.

Confusing sentences for me in "Deep Learning, NLP, and Representations"

Hello, Mr. Olah.

First thing first, thank you for your great work. I am learning with pleasure via your articles.

Here I would like to address what is difficult for me to understand.
The below two sentences are from the source of the section "Shared Representations":

This general tactic ... One of the great strengths of this approach is that it allows the representation to learn from more than one kind of data.

There’s a counterpart to this trick. Instead of learning a way to represent one kind of data and using it to perform multiple kinds of tasks, we can learn a way to map multiple kinds of data into a single representation!

It was kind of confusing for me, because "the trick" and its "counterpart" seem to have the similar descriptions. And below is my current understanding.

For the first one, the representation can learn other kind of data, incrementally, whenever other tasks come in and the word embedding tries to solve the tasks. And for the second one (its counterpart), assuming we already have multiple tasks and its corresponding multiple kinds of data, then the single representation can learn these all data.

Since I have worked this article for the translation in Korean, it would be great if my understanding gets confirmed and corrected.

Best regards,
Don

colah / colah.github.io Goto Github PK

colah.github.io's People

Contributors

Stargazers

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colah.github.io's Issues

Enable RSS feed auto-discovery

Change Wording In ConvNet Post

Blog Setup

Can I quote your picture about RNN in my paper？

No automatic redirection from HTTP to HTTPS

What tool are you using for drawing recurrent neural network?

hidden state not described in Understanding LSTMs

Wrong labels in LSTM diagram

Your figures are too good

Confusing sentences for me in "Deep Learning, NLP, and Representations"

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