30 citations · 30 across the 1 of their papers we have counts for
4 papers
Model Bridging: Connection between Simulation Model and Neural Network
Keiichi Kisamori, Keisuke Yamazaki, Yuto Komori +1
The interpretability of machine learning, particularly for deep neural networks, is crucial for decision making in real-world applications. One approach is replacing the un-interpr…
Simulator Calibration under Covariate Shift with Kernels
Keiichi Kisamori, Motonobu Kanagawa, Keisuke Yamazaki
We propose a novel calibration method for computer simulators, dealing with the problem of covariate shift. Covariate shift is the situation where input distributions for training…
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…
Stochastic complexity of Bayesian networks
Keisuke Yamazaki, Sumio Watanbe
Bayesian networks are now being used in enormous fields, for example, diagnosis of a system, data mining, clustering and so on. In spite of their wide range of applications, the st…