1 citations · 1 across the 4 of their papers we have counts for
4 papers
Two stages domain invariant representation learners solve the large co-variate shift in unsupervised domain adaptation with two dimensional data domains
Hisashi Oshima, Tsuyoshi Ishizone, Tomoyuki Higuchi
Recent developments in the unsupervised domain adaptation (UDA) enable the unsupervised machine learning (ML) prediction for target data, thus this will accelerate real world appli…
Aortic root landmark localization with optimal transport loss for heatmap regression
Tsuyoshi Ishizone, Masaki Miyasaka, Sae Ochi +2
Anatomical landmark localization is gaining attention to ease the burden on physicians. Focusing on aortic root landmark localization, the three hinge points of the aortic valve ca…
Ensemble Kalman Variational Objectives: Nonlinear Latent Trajectory Inference with A Hybrid of Variational Inference and Ensemble Kalman Filter
Tsuyoshi Ishizone, Tomoyuki Higuchi, Kazuyuki Nakamura
Variational inference (VI) combined with Bayesian nonlinear filtering produces state-of-the-art results for latent time-series modeling. A body of recent work has focused on sequen…
Real-time Linear Operator Construction and State Estimation with the Kalman Filter
Tsuyoshi Ishizone, Kazuyuki Nakamura
The Kalman filter is the most powerful tool for estimation of the states of a linear Gaussian system. In addition, using this method, an expectation maximization algorithm can be u…