State Space Models: A Modern Approach

State Space Models: A Modern Approach

State Space Models
Hidden Markov Models
Linear-Gaussian SSMs
Extended (linearized) methods
Unscented methods
- Unscented filtering
- Unscented smoothing
Quadrature and cubature methods
Posterior linearization
Assumed Density Filtering
Variational inference
Particle filtering
Sequential Monte Carlo
Offline parameter estimation (learning)
Multi-target tracking
Data assimilation using Ensemble Kalman filter
Bayesian non-parametric SSMs
Changepoint detection
Timeseries forecasting
Markovian Gaussian processes
Differential equations and SSMs
Optimal control
Bibliography

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Parallel HMM smoothing

Parallel HMM smoothing¶

[HSarkkaGarciaFernandez21]

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Forwards-filtering backwards-sampling algorithm

By Kevin Murphy, Scott Linderman, et al.
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