luca
@fahrenheit
ML researcher, interested in math and probabilistic machine reasoning.
luca
moments are important theoretically because they provide an alternative way to fully and uniquely specify a probability distribution, a fact that is intuitive if you understand how moment’s quantify a distribution’s location, spread, and shape
Understanding Moments
This is so good.
probably the right way to understand the right in the Uk..
The glow in the centre of the k-space image represents the lower spatial frequencies, which contains the bulk of the image contrast information. As we move away from this central glow, the finer details and edges, representing the higher spatial frequencies
Nadav Levi • Visualising MRI data in Python
The Fisher information matrix is simply the Hessian of KL divergence at the point where two distributions are equal.