Tab-PFN explained via Japanese puzzle books: inferring the problem from the data itself
PTenigma · x · 2026-11-07
The author explains Tab-PFN, a fairly new and counterintuitive tabular ML method, with an analogy: solving Japanese puzzle books you can't read — you must first guess the rules, then solve; fail either step and you're stuck.
Rather than training for a specific task, Tab-PFN uses amortised Bayesian inference to figure out what kind of problem it's facing from the structure of the data, then solves it directly — effectively "guessing the rules" before solving.
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