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
The risk in designing any personal knowledge system lies in the overemphasise of the acquisition system to the detriment of the review system. Acquisition can masquerade as work, but collecting without review is pseudo-work.
The Fisher information matrix is simply the Hessian of KL divergence at the point where two distributions are equal.
Metacademy - Differential geometry for machine learning
Only the future can tell. But we need to mend our ways. Otherwise, nihilism will win and we will deconstruct ourselves into oblivion. Maybe this is will be the million dollar question of the next century. What do we do, when we do not have to do anything?
refinement | llct
The paranoid fantasy behind Brexit | Brexit | The Guardian
amp.theguardian.com
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
Fino alla fine, con gli occhi aperti e il cuore saldo. A testa alta - sempre.
Until the end, with eyes open and a steady heart. Head held high - always.
— 5th May 2025 5:20 AM, somewhere in London
However, there’s a third way to think about the first moment, and it’s the one that I think is most useful for understanding moments generally: the first moment tells us how far away from the origin the center of mass is. I like this interpretation because it is analogous to a moment arm in mechanics, which is the length of an arm between an axis o... See more