Search Results for author: Matthew M. Dunlop

Found 2 papers, 0 papers with code

Large Data and Zero Noise Limits of Graph-Based Semi-Supervised Learning Algorithms

no code implementations23 May 2018 Matthew M. Dunlop, Dejan Slepčev, Andrew M. Stuart, Matthew Thorpe

Scalings in which the graph Laplacian approaches a differential operator in the large graph limit are used to develop understanding of a number of algorithms for semi-supervised learning; in particular the extension, to this graph setting, of the probit algorithm, level set and kriging methods, are studied.

Dimension-Robust MCMC in Bayesian Inverse Problems

no code implementations9 Mar 2018 Victor Chen, Matthew M. Dunlop, Omiros Papaspiliopoulos, Andrew M. Stuart

One popular formulation of such problems is as Bayesian inverse problems, where a prior distribution is used to regularize inference on a high-dimensional latent state, typically a function or a field.

Active Learning Efficient Exploration +4

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