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#bayesian

1 post1 participant0 posts today
Public
Daniel Lakeland

aeon.co/essays/no-schrodingers

This is a pretty good article for showing how confused the interpretation of QM is. And its a good article to understand why i personally side with Bohm and Bell in thinking the pilot wave theory is the one most reasonable to believe. Because the pilot wave theory has the following quality. The theory is a mapping from initial position at time t=0 to final position at time t=1...Its deterministic, but our knowledge of the initial condition is not
#quantum #bohm #bayesian

<p>Illustration by <a href="https://www.claytonjunior.com/" target="_blank" rel="noreferrer noopener">Clayton Junior</a></p>
AeonNo, Schrödinger’s cat is not alive and dead at the same time | Aeon EssaysThe weird paradox of Schrödinger’s cat has found a lasting popularity. What does it mean for the future of quantum physics?
Public
Paul Healey

open.substack.com/pub/thefucki #MagicalTrump #RealTrump, so all you get with the #Bayesian factor is reality without the navigator, just the chaos; the illusion of randomness, the collapse and the sinking? An Emperor is no Deity, no constitution of the categories foundation, just an aimless clown deluded by the opium of his cult and the grandeur of its Nazi oligarchs. #Poll #Polls #NaziOligarchs #GreatLiars

The Fucking News · Real-Trump Losing in the Polls to Lying Campaign-TrumpBy Jonathan Larsen
Public
Steven

Hot off the press - our report on gender disparities in grant seeking at the University of Cambridge (who applies for and who gets research grant funding).

bennettinstitute.cam.ac.uk/pub

The story:
1) The structural disparities are big (not so surprising)
2) The patterns of disparity at particular grades in particular disciplines go both ways (more surprising)

#ResearchPolicy
#ResearchGrants
#GenderDifferences
#Bayesian

If you like graphs, you'll probably like it!

View through an old window in Old Schools.
#RandomCambridgeWindowPicture
Replied in thread
Public
pglpm

@Posit

It's important to emphasize that "realistic-looking" data does *not* mean "realistic" data – especially high-dimensional data (unfortunately that post doesn't warn against this).

If one had an algorithm that generated realistic data for a given inference problem, it would mean that that inference problem had been solved. So: for educational purposes, why not. But for validation-like purposes, use with uttermost caution and at your own peril.

#rstats#statistics#bayesian
Public *
Manuel Baltieri

After a long collaboration with @martinbiehl, @mc and @Nathaniel I’m excited to share the first of (hopefully) many outputs:
“A Bayesian Interpretation of the Internal Model Principle”
arxiv.org/abs/2503.00511.

This work combines ideas from control theory, applied #categorytheory and #Bayesian reasoning, with ramifications for #cognitive science, #AI/#ML, #ALife and biology to be further explored in the future.

In these fields, we come across ideas of “models”, “internal models”, “world models”, etc. but it is hard to find formal definitions, and when one does, they usually aren’t general enough to cover all the aspects these different fields consider important.

In this work, we focus on two specific definitions of models, and show their connections. One is inspired by work in control theory, and one comes from Bayesian inference/filtering for cognitive science, AI and ALife, and is formalised with Markov categories.

In the first part, we review and reformulate the “internal model principle” from control theory (at least, one of its versions) in a more modern language heavily inspired by categorical systems theory (davidjaz.com/Papers/DynamicalB, github.com/mattecapu/categoric).

Public
Alex Holcombe

A #bayesian blogpost, by two of my undergraduate students! It's their report on their learning Bayesian modeling by applying it to my lab's data.
alexholcombe.github.io/brms_ps
Summary: we learned to use brms. But had trouble when we added more than one or two factors to the model. Little idea why; haven't had time to tinker much with that.

alexholcombe.github.ioBayesian analysis of psychophysical data using brms
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