Thanks for the correction on the gini of the gaussian. Why do you think the toy model in the Yakovenko papers are to be taken seriously? We can't possibly have a society w/ a normal wealth distribution. In Yakovenko's ABMs agents interact at random, it lacks a certain realism.

Thanks. What are the implications of a wealth distribution with a gini coefficient of 0.5? I think the gaussian distribution has a gini approximately equal to 0.5.
In your example, the wealth is mainly coming from income and not capital?

curious, wheres the number 0.5 coming from?

You wrote a very good caption!?

Fits my experience coming from physics, networks and going into ML not being a computer scientist. It's harder to find like minded peers in industry though doable. It's gotta a little easier for me once I started focusing on more mainstream/core topics in ML.

agree though I wonder if symmetric matrices aren't just convenient. For example with covariance matrices depending on what one tries to model symmetry can muddy the water (i.e. the intensity and directionality of dependence matters)

You cannot trust anything on that platform which remotely tries to get a reaction out of you.

There you go

Reverse psychology.

90k

it's been a constant reminder that quantum mechanics has so much interesting mathematics but also the problems solved share so much with statistical learning but it's presented in a totally different way.