Some personal resources for understanding and applying singular learning theory. For more information, please read the textbook by Sumio Watanabe.

Thesis | Algebraic methods for evaluating integrals in Bayesian statistics |

Preprint | Asymptotic approximation of marginal likelihood integrals |

Notes | Useful facts about RLCT |

Slides | What is singular learning theory? |

Slides | Singular Learning Theory: A view from Algebraic Geometry |

Slides | Computing resolutions: how and why |

Slides | Computing integral asymptotics using toric blow-ups of ideals |

Video | Studying model asymptotics with Singular learning theory |

Website | Macaulay2 library for computing RLCTs using Newton polyhedra |

My slides and problem sets on Singular Learning Theory from the Motivic Invariants and Singularities workshop at the Center for Mathematics at Notre Dame (May 2013).