(this post is by Charles)
This September, the Interuniversity Institute for Biostatistics and statistical Bioinformatics is holding its 5th Summer School on Advanced Bayesian Methods. The event is set to take place in Leuven, Belgium. From their webpage:
As before, the focus is on novel Bayesian methods relevant to the applied statistician. In the fifth edition of the summer school, the following two courses will be organized in Leuven from 11 to 15 September 2023:
- Three-day course (11-13 September) on Bayesian Workflow for hierarchical and ODE-based models using Stan by Dr. Charles Margossian (Flatiron Institute, Center for Computational Mathematics in New York)
- Two-day course (14-15 September) on Spatial modeling with inlabru in ecology and beyond — background and practice by Prof. Janine Illian (University of Glasgow, UK)
The target audience of the summer school are statisticians and/or epidemiologists with a sound background in statistics, but also with a background in Bayesian methodology. In both courses, practical sessions are organized, so participants are asked to bring along their laptop with the appropriate software (to be announced) pre-installed.
I’m happy to do a three-day workshop on Stan: we’ll have ample time to dig into a lot of interesting topics and students will have a chance to do plenty of coding.
I’m also looking forward to the course on spatial modeling. I’ve worked quite a bit on the integrated Laplace approximation (notably its implementation in autodiff systems such as Stan), but I’ve never used the INLA package itself (or one of its wrappers), nor am I very familiar with applications in ecology. I expect this will be a very enriching experience.
The registration deadline is July 31st.
This looks great! Also, I recommend the waffles.
I hope this suggestion is ok.
When at 5th Summer School on Advanced Bayesian Methods, some discussion at the water cooler of Friston may yield some fresh insights. Even if too left field, the tension when mentioning Friston will compel new connections.
Here is a recent discussion & links on the new:
“The Canal Papers
“The First Canal Paper
“You know all the stuff we’ve been talking about here the past few years – mental mountains, trapped priors, relaxed beliefs under psychedelics? The new keyword for all of that is “canalization”. At least that’s what I gather from a giant paper recently published by some of the leading thinkers in computational psychiatry (Karl Friston, Robin Carhart-Harris, etc).
“A quick review: you can model the brain as an energy landscape . . .
[graphic]
https://astralcodexten.substack.com/p/the-canal-papers
https://slatestarcodex.com/2018/03/04/god-help-us-lets-try-to-understand-friston-on-free-energy/
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In “THE LURE OF FREE ENERGY” linked by Scott Alexander above, Schwartz provides lucid explanations, critique and suggested niches for Friston et al active inference aka free energy.
01 Dec 2013.
WOLFGANG SCHWARZ
(a commenter updates free energy to active inference)
# RyanB on 18 November 2018, 07:38 ” Regarding the confusing term, in an interview published in February, Friston said “we have now taken to referring to the free energy principle as active inference, which seems closer to the mark and slightly less pretentious for non-mathematicians.”
https://www.aliusresearch.org/uploads/9/1/6/0/91600416/friston_-_of_woodlice_and_men.pdf
https://www.aliusresearch.org/uploads/9/1/6/0/91600416/alius_bulletin_n%C2%B02__2018_.pdf
…
https://www.umsu.de/wo/2013/600
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Only found one w Friston in a statmodeling post:
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC
“Lindley’s paradox”
Posted on May 31, 2012 9:58 AM by Andrew
“Sam Seaver writes:
“I [Seaver] happened to be reading an ironicarticle by Karl Friston when I learned something new about frequentist vs bayesian, namely Lindley’s paradox, on page 12. The text is as follows:
…
https://statmodeling.stat.columbia.edu/2012/05/31/lindleys-paradox/
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Gelman & Friston:
“Bayesian model selection maps for group studies”
…
“The product of the analysis procedures described in this paper are posterior probability maps. These show voxels where the posterior probability over model frequency exceeds some user-specified value. In a previous work (Friston and Penny, 2003), we have derived PPMs over effect size. We note that, as is common-place in Bayesian inference, these posterior inferences could be augmented with the use of decision theory. This requires the costs of false negative and false-positive decisions to be specified. One can then use decision theory to make decisions which minimise, for example, the posterior expected loss (Gelman et al., 1995). In addition, we note a connection between posterior probabilities and false discovery rate, in which if above threshold values are declared as activations, a posterior probability of greater than 95% implies a rate of false discoveries less than 5% (Friston and Penny, 2003).
…
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2791519/
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Friston says: “… I use ‘reasoning’ here to mean explanations that arise from inference or abduction – that is, trying to account for observations in terms of latent causes, rules or principles.
“This perspective on process leads us to an elegant, if rather deflationary, story about why the mind exists. Inference is actually quite close to a theory of everything – including evolution, consciousness, and life itself. It is abduction all the way down. We are thrown into the world as a process already in motion; and processes can only reason towards what is ‘out there’ based on sparse (if carefully selected) samples of the world. This view dissolves familiar dialectics between mind and matter, self and world, and representationalism (we depict reality as it is) and emergentism (reality comes into being through our abductive encounters with the world). But just how did inference happen before there were inferrers around to do it? How did inert matter ever begin the processes that led to consciousness?”
https://aeon.co/essays/consciousness-is-not-a-thing-but-a-process-of-inference
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Abduction in “Where do theories come from?”
Posted on May 17, 2013
…
AG: “I found this very difficult to read and forwarded it to Cosma Shalizi, who writes: “… if there’s a role for abduction, it’s there, in explicating the “generate” part of generate-and-test. (In fact, if memory serves, Peirce later repented of his term “abduction”, and just called it “hypothesis” or “hypothesizing”.)”…
…
“Sechrest wrote: “… To me, abduction seems more likely to occur in the aftermath of having seen something. Isaac Asimov once said The most exciting phrase to hear in science, the one that heralds new discoveries, is not ‘Eureka!’ but ‘That’s funny…’
“And that is when abduction begins, the attempt to identify explanations and reason toward the best one.”…
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“The event is set to take place in Leuven, Belgium.”
If you attend this event, note the following: Leuven is, to the surprise of most people, the center of banana research in the entire world. Furthermore, there are zero banana trees in this world and the Bible mistakenly refers to Eve’s fig leaf when it really was a banana leaf. To find out more, read this fascinating book by Dan Koeppel:
Banana: The Fate of the Fruit That Changed the World
This looks amazing. However, it is clearly an “advanced” summer school. Any recommendations on where to start to get a proper foundation on Bayesian Statistics in 2023? Thank you very much!