12 citations · 20 across the 7 of their papers we have counts for
Showing 2016Show all
2 papers · 1 filter
stat.ML2016
Mean-Field Variational Inference for Gradient Matching with Gaussian Processes
Nico S. Gorbach, Stefan Bauer, Joachim M. Buhmann
Gradient matching with Gaussian processes is a promising tool for learning parameters of ordinary differential equations (ODE's). The essence of gradient matching is to model the p…
stat.ML2016★ 2 cited
Model Selection for Gaussian Process Regression by Approximation Set Coding
Benjamin Fischer, Nico Gorbach, Stefan Bauer +2
Gaussian processes are powerful, yet analytically tractable models for supervised learning. A Gaussian process is characterized by a mean function and a covariance function (kernel…