What about Polynomial growth: https://oeis.org/wiki/Growth_of_sequences#Polynomial
Exponential Growth and Covid-19 [video]
21–30 of 135 posts
Re: Exponential Growth and Covid-19 [video]
#22Seems to have a much lower hospitalized mortality rate than 2017 flu https://www.google.com/amp/s/www.livescience.com/amp/new-cor...
Re: Exponential Growth and Covid-19 [video]
#23Earlier quoted context omitted.
If the curve has flatlined in China and only 20,283 remain, China should not have a further problem with resources. The rest of the world, of course, is just getting started.
What happens when infected soul from US / other place visits china ? Is there an immunity built up in infected people or does the clock reset ? You cant quarantine the world and expect a global economy to survive
Gotta love the people that see people dying and are most concerned about the economy.
Re: Exponential Growth and Covid-19 [video]
#24Seems to have a much lower hospitalized mortality rate than 2017 flu https://www.google.com/amp/s/www.livescience.com/amp/new-cor...
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Re: Exponential Growth and Covid-19 [video]
#25The video says that it's really a logistic curve. Which is also the activation function (sigmoid) in a few machine learning articles that I've been reading. https://en.wikipedia.org/wiki/Sigmoid_function https://en.wikipedia.org/wiki/Logistic_function Can anyone recommend anything to read to add more clarity? Why does this appear in deep learning too?
For neural networks to work, the activation function has to be nonlinear and monotonic. In order to be able to apply the chain rule for training the weights by backpropagation, the function also has to be differentiable. The logistic function is one obvious choice, but other functions such as tanh, arctan or relu are popular as well.
Re: Exponential Growth and Covid-19 [video]
#26I've been tracking the coronavirus news for the past few weeks and have found https://www.reddit.com/r/covid19 to be good for tracking the latest scientific/medical publications, and https://www.reddit.com/r/coronavirus for general news. For transmission rates, this team is updating their modeling results often: https://cmmid.github.io/topics/covid19/current-patterns-tran... On twitter, @datagraver is publishing some…
This is a good dashboard tracker as well:
Re: Exponential Growth and Covid-19 [video]
#27The video says that it's really a logistic curve. Which is also the activation function (sigmoid) in a few machine learning articles that I've been reading. https://en.wikipedia.org/wiki/Sigmoid_function https://en.wikipedia.org/wiki/Logistic_function Can anyone recommend anything to read to add more clarity? Why does this appear in deep learning too?
In machine learning it's used as an activation function. Activation functions are used to add non-linearity to the model. I think sigmoid functions are inspired from neurons, but I'm not sure exactly how. Nowadays, ReLU activations are used more often than sigmoidals because they are quicker to compute.
Re: Exponential Growth and Covid-19 [video]
#28The video says that it's really a logistic curve. Which is also the activation function (sigmoid) in a few machine learning articles that I've been reading. https://en.wikipedia.org/wiki/Sigmoid_function https://en.wikipedia.org/wiki/Logistic_function Can anyone recommend anything to read to add more clarity? Why does this appear in deep learning too?
In machine learning it's used as an activation function. Activation functions are used to add non-linearity to the model. I think sigmoid functions are inspired from neurons, but I'm not sure exactly how. Nowadays, ReLU activations are used more often than sigmoidals because they are quicker to compute.
>I think sigmoid functions are inspired from neurons
I mean the use of sigmoids as activations in NNs
Re: Exponential Growth and Covid-19 [video]
#29I've been tracking the coronavirus news for the past few weeks and have found https://www.reddit.com/r/covid19 to be good for tracking the latest scientific/medical publications, and https://www.reddit.com/r/coronavirus for general news. For transmission rates, this team is updating their modeling results often: https://cmmid.github.io/topics/covid19/current-patterns-tran... On twitter, @datagraver is publishing some…
Both of those subs are incredibly tinfoily and panicky. Honestly reddit is the worst. And BI is right that they are doing the same as always, just consiparcy things https://www.businessinsider.com/coronavirus-reddit-social-pl... Also you might as well rename /r/Coronavirus/ to /r/politics2 aka fucktrump. It's the same thing over and over again
/r/Coronavirus used to have some info on it. But yeah, for the past week+ (since Reddit began linking it on the front page, maybe?) every other article has been "the US isn't testing enough", and the comments of every article have degenerated into "Trump is literally evil, this is all being done for the benefit of corporations, he just wants to protect the stock market" which is really not helpful.
It might (or might not) be accurate, but that's kinda irrelevant.
Re: Exponential Growth and Covid-19 [video]
#30The video says that it's really a logistic curve. Which is also the activation function (sigmoid) in a few machine learning articles that I've been reading. https://en.wikipedia.org/wiki/Sigmoid_function https://en.wikipedia.org/wiki/Logistic_function Can anyone recommend anything to read to add more clarity? Why does this appear in deep learning too?
In machine learning it's used as an activation function. Activation functions are used to add non-linearity to the model. I think sigmoid functions are inspired from neurons, but I'm not sure exactly how. Nowadays, ReLU activations are used more often than sigmoidals because they are quicker to compute.
ReLu are mainly used because in practice they show better results than sigmoids in many areas. The fact that they are also faster to compute is just a nice side effect.