A general recipe for constructing tuning-free, asymptotically exact variational flows from general involutive MCMC kernels.

Convergence analysis and experiments of a new label model.

We present AutoDiscovery, a method for open-ended scientific discovery that uses Bayesian surprise and Monte Carlo tree search to sample diverse hypotheses at scale that are likely to lead to discoveries that are suprising both to LLMs and humans.