The thesis derives an analytic family of Riemannian metrics on the Gromoll-Meyer exotic 7-sphere via Kaluza-Klein reduction, identifies the maximal-isometry case, and introduces a machine-learning algorithm for finding Einstein metrics on general manifolds.
Reports on Progress in Physics , abstract =
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The original conclusions stand: standard Bayesian posterior computations using conditional densities remain physically inconsistent under change of variables, and Yan et al.'s defense does not resolve this.
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A Physicist's Visit to Exotic Spheres
The thesis derives an analytic family of Riemannian metrics on the Gromoll-Meyer exotic 7-sphere via Kaluza-Klein reduction, identifies the maximal-isometry case, and introduces a machine-learning algorithm for finding Einstein metrics on general manifolds.
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Response to: "A note on conditional densities, Bayes' rule, and recent criticisms of Bayesian inference" by Yan et al., 2026
The original conclusions stand: standard Bayesian posterior computations using conditional densities remain physically inconsistent under change of variables, and Yan et al.'s defense does not resolve this.