It is always good to be careful when using random number generators. Things might not be as random as they seem. I …
I bought the Day One app and it made me very happy
I have been experimenting with ways of keeping a journal for my research since I started my PhD. I have done everything …
Chaining function calls in Matlab
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Matlab has a nice feature that lets you chain commands by treating functions as variables. This means that you can write: a …
Saving from inside a parfor loop in Matlab
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If you call save from a parfor loop in Matlab, like this for example: parfor k=1:100 foo = exp(-k); save([’myfile’,num2str(k),’.mat’],’foo’); endparfor k=1:100 …
Making function returns in Matlab compact
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I used to write this in Matlab: foo1 = zeros(1,100); foo2 = cell(1,100); for i = 1:100 [tmpFoo1, tmpFoo2] = foo ( …
Understanding the Metropolis Hasting algorithm – A tutorial
The Problem Say you want to evaluate the expectation of a function over a random variable $$E[f(x)] = \int p(x)f(x)dx$$, or perhaps …
A short tutorial on Kernel Density Estimation (KDE)
The aim of Kernel Density Estimation(KDE) is: Given a set of $$N$$ samples from a random variable, $$\mathbf{X}$$, possibly multivariate and continuous, …
The psychology of debugging – the bias of complexity
Most of the times when you are writing code you are make mistakes either in the structure or in the specific code. …
The start-up evangelic
Attended the Stockholm Start-up Day 2013 event. It was really fun and the event was well organized with a good flow. It is …
Partially fixing numerical underflow for mixture models
In a mixture model the probability of an event $$x$$ is written $$P(x=X) =\sum_{i}\pi_{i}P_{i}(x=X) $$, where $$\pi_{i}$$ is the probability of the …