2 citations · 2 across the 5 of their papers we have counts for
6 papers
Interpretable Graph Partitioning for Spatial Prediction
Yuta Shikuri
Spatial prediction estimates unobserved values from spatially distributed observations. Although flexible predictive models are increasingly available, their practical use remains…
Surrogate Graph Partitioning for Spatial Prediction
Yuta Shikuri, Hironori Fujisawa
Spatial prediction refers to the estimation of unobserved values from spatially distributed observations. Although recent advances have improved the capacity to model diverse obser…
Learning Survival Models with Right-Censored Reporting Delays
Yuta Shikuri, Hironori Fujisawa
Survival analysis provides statistical methods to model the time until an event occurs. Reporting delays arise when event times are not observed at their occurrence but are only re…
Learning from Summarized Data: Gaussian Process Regression with Sample Quasi-Likelihood
Yuta Shikuri
Gaussian process regression is a powerful Bayesian nonlinear regression method. Recent research has enabled the capture of many types of observations using non-Gaussian likelihoods…
Likelihood-Free Gaussian Process for Regression
Yuta Shikuri
Gaussian process regression can flexibly represent the posterior distribution of an interest parameter given sufficient information on the likelihood. However, in some cases, we ha…
Decomposed Quadratization: Efficient QUBO Formulation for Learning Bayesian Network
Yuta Shikuri
Algorithms and hardware for solving quadratic unconstrained binary optimization (QUBO) problems have made significant recent progress. This advancement has focused attention on for…