p(x|y) as a nonlinear correlation metric?
Correlation captures a narrow kind of dependence: linear association between variables. Could comparing conditional distributions, \(p(x \mid y)\), provide a more general way to character...
A working map of random ideas and thoughts: questions, half-formed connections, things I’m reading, and small experiments. Leaving this deliberately unpolished to see how my thoughts evolve.
Correlation captures a narrow kind of dependence: linear association between variables. Could comparing conditional distributions, \(p(x \mid y)\), provide a more general way to character...
The retina is not simply a camera that forwards pixels. Its output is already a transformed representation of the visual scene. What are the relevant constraints behind that transformatio...
The Schur complement appears in the conditional covariance of jointly Gaussian random variables. It seems to isolate the part of \(X\)’s variability that remains after accounting for \(Y\).
A representation that ignores nuisance variation can make downstream decisions easier. But invariance is also information loss: distinctions in the input are deliberately collapsed.
Mises argued in 1920 that a planned economy can’t work: with no prices there’s no way to express what anything costs in terms of everything else. Lange said fine, the planner solves the e...
Try long division in Roman numerals. The algorithm isn’t harder, the notation just won’t hold the intermediate state.
Scale works and it costs more every year.
Until the 1840s every English town ran on local solar time. Bristol sat about ten minutes behind London and nobody minded, because nothing moved fast enough for it to matter.
Rather than treating noise only as something to remove, use it as a way to interrogate a representation. Perturb the input, intermediate features, or readout and ask which changes matter ...
Excel probably has more users than every programming language combined, and most of them wouldn’t say they write code.
Transformers showed up at the same time as a jump in data and compute, so the two are hard to pull apart.
Beck’s 1933 diagram is wrong about distance nearly everywhere and is the better map for it. Riders want stop counts and interchanges, not geography.
Model systems get picked for how easy they are to work with. Immortalized lines, 2D monolayers, one cell type, no mechanical load. Each is a step away from the thing you’re modeling, and ...
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