Bayesian Quadrature on Riemannian Data Manifolds

Repository for the paper "Bayesian Quadrature on Riemannian Data Manifolds" (ICML 2021). See https://proceedings.mlr.press/v139/frohlich21a/frohlich21a.pdf

This code includes the core of the LAND mixture model (geodesic methods + optimization + quadrature) and a Bayesian quadrature (BQ) implementation based on the ''bayesquad'' library (see bayesquad/LICENSE). A small demo is included in the file demo.py, which shows how to fit a LAND mixture using MC or BQ.

Requirements:

• python==3.7.7
• gpy==1.9.9
• pymanopt==0.2.5
• scikit-learn==0.23.1
• scipy==1.5.2
• dill==0.3.3
• multimethod==1.4