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Common sense says that what you believe after seeing new data should be some sort of compromise between what you believed before and what the new data says. You don’t want to ignor...
Beyond the teaching question, this is an interesting topic on its own: thinking about classical statistical ideas of point estimation, hypothesis testing, and uncertainty quantific...
by Marie Chion, Arthur Leroy Differential analysis is a routine procedure in the statistical analysis toolbox across many applied fields, including quantitative proteomics, the ma...
More informed decision-making through uncertainty quantification The post Beyond Point Predictions: A Practical Introduction to Bayesian Neural Networks appeared first on Towards D...
When I first started working on posterior predictive checking back in 1988, it was as a device for determining equivalent degrees of freedom for a chi-squared test for a model with...
I see at least three updates one might make from the recent OAI/Hugging Face hacking incident: 1. “This happened sooner than I expected, and the story is more dramatic than I expec...
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Our wonderful new Bayesian Workflow book is now available as a free pdf! Just go the link—it’s right there! I recommend getting the hard copy too because you’ll want to be able to...
I took a look at the above-titled book by economists Duncan Foley and Ellis Scharfenaker. It’s an interesting read, in many ways a throwback to the 1950s when a group of mathematic...
A few days ago I wrote a post entitled Does additional data always reduce posterior variance?. In a nutshell, the answer is no, not always. That led the previous post which looked...
Using artificial intelligence to decide where the next Euro goes.Continue reading on Berlin Tech Blog (by mobile.de & Kleinanzeigen) »
AI systems should not automate a decision simply because they can provide a prediction. A decision system should consider how uncertain the prediction is and defer if a mistake wou...
What if the probability distribution underlying your parameter estimation algorithm is the reason you’re getting the wrong answer?Continue reading on Medium »
Roughly speaking, Bayesian Workflow is to Bayesian Data Analysis in 2026 what Bayesian Data Analysis was to earlier Bayesian books in 1995: it builds upon everything that came befo...
by Nadav Ben Nun, Saharon Rosset, David Gresham, Yoav Ram High-throughput experimental platforms now routinely generate data from dozens or hundreds of independent observations. S...
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