I have to finish my NSF proposal with Mike Blanton (NYU), so naturally I am in procrastination mode. Here are three papers I wish I would write. Maybe I should post them on my ideas blog:
Occam's Razor is wrong: This paper, co-authored with Jennifer Hill (NYU), would be about the fact that, in the real, observed world, the simplest explanation is always wrong or at least incomplete.
Causation is just causality: This paper, maybe co-authored with David Blei (Columbia) or Bernhard Schölkopf (MPI-IS) or Hill, shows that you don't need to have free will in order to have cogent causal explanations of data. That is, you don't need to phrase causality in terms of predictions for counter-factual experiments that you might have chosen to do.
You don't ever want evidence: This paper shows that any time you are computing the Bayesian evidence—what I call the fully marginalized likelihood (fml)—you are doing the wrong integral and solving the wrong problem. For both practical and theoretical (principled) reasons.
"For every complex problem, there is a solution which is simple, elegant, and wrong" (at least I think thatʻs how the quote from Mencken goes)
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