2 citations · 2 across the 7 of their papers we have counts for
15 papers
Machine-Learning Emulation of Satellite Greenhouse Gas Retrievals: Stability over Time
Nugzar Gognadze, Motonobu Kanagawa, Yu Someya +1
Retrieval algorithms are used to estimate atmospheric concentrations of greenhouse gases (GHGs), such as carbon dioxide (CO2) and methane (CH4), by solving inverse problems from hi…
Predictive Uncertainty in Short-Term PV Forecasting under Missing Data: A Multiple Imputation Approach
Parastoo Pashmchi, Jérôme Benoit, Motonobu Kanagawa
Missing values are common in photovoltaic (PV) power data, yet the uncertainty they induce is not propagated into predictive distributions. We develop a framework that incorporates…
kNNSampler: Stochastic Imputations for Recovering Missing Value Distributions
Parastoo Pashmchi, Jérôme Benoit, Motonobu Kanagawa
We study a missing-value imputation method, termed kNNSampler, that imputes a given unit's missing response by randomly sampling from the observed responses of the most similar…
Gaussian Processes and Reproducing Kernel Hilbert Spaces: Connections and Equivalences
Motonobu Kanagawa, Philipp Hennig, Dino Sejdinovic +1
This monograph studies the relations between two approaches using positive definite kernels: probabilistic methods using Gaussian processes, and non-probabilistic methods using rep…
Variable Selection for Comparing High-dimensional Time-Series Data
Kensuke Mitsuzawa, Margherita Grossi, Stefano Bortoli +1
Given a pair of multivariate time-series data of the same length and dimensions, an approach is proposed to select variables and time intervals where the two series are significant…
Fast Computation of Leave-One-Out Cross-Validation for -NN Regression
Motonobu Kanagawa
We describe a fast computation method for leave-one-out cross-validation (LOOCV) for -nearest neighbours (-NN) regression. We show that, under a tie-breaking condition for ne…