most citedEnsemble Kalman Variational Objectives: Nonlinear Latent Trajectory Inference with A Hybrid of Variational Inference and Ensemble Kalman Filter

1 citations · 1 across the 3 of their papers we have counts for

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3 papers

stat.CO2021

The Application of Zig-Zag Sampler in Sequential Markov Chain Monte Carlo

Yu Han, Kazuyuki Nakamura

Particle filtering methods are widely applied in sequential state estimation within nonlinear non-Gaussian state space model. However, the traditional particle filtering methods su…

stat.ML2020★ 1 cited

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…

stat.CO2020

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…