2 papers
stat.ML2019
Model Selection for Simulator-based Statistical Models: A Kernel Approach
Takafumi Kajihara, Motonobu Kanagawa, Yuuki Nakaguchi +2
We propose a novel approach to model selection for simulator-based statistical models. The proposed approach defines a mixture of candidate models, and then iteratively updates the…
stat.ML2018
Kernel Recursive ABC: Point Estimation with Intractable Likelihood
Takafumi Kajihara, Motonobu Kanagawa, Keisuke Yamazaki +1
We propose a novel approach to parameter estimation for simulator-based statistical models with intractable likelihood. Our proposed method involves recursive application of kernel…