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Showing 1 to 5 of 5 for “"sequential inference"”.

  1. Parameterizing transport maps for ensemble data assimilation

    … and experiments for employing these maps for inference, particularly examining the map parameterization for this function approximation problem. Using these ingredients, we introduce and discuss an algorithm that uses transport to perform online inference of the static parameters of an SSM, …

    mit Repository record for Parameterizing transport maps for ensemble data assimilation (opens in a new tab)

  2. Inference and decision making in large weakly dependent graphical models

    … to a given query. This can be implemented in a sequential manner – whereby knowledge from items that have already been screened is used to assist in the selection of subsequent items to screen. Often the items being searched have an underlying network structure. Using the network structure and a …

    lancaster Repository record for Inference and decision making in large weakly dependent graphical models (opens in a new tab)

  3. Sampled ancestors and dating in Bayesian phylogenetics

    … and temporal fossil data) in one joint inference which contrasts with the sequential inference of the calibration methods. I apply total-evidence dating which allows sampled ancestors to a penguin dataset to reveal a very recent (compared to previous estimates) crown penguin radiation.

    auckland-ms Repository record for Sampled ancestors and dating in Bayesian phylogenetics (opens in a new tab)

  4. Non-Gaussian Stochastic Process Priors for Learning

    … previously intractable for simulation and use in inference. We show that these simulation algorithms enable Monte Carlo inference directly in the function space of continuous-time systems based on stochastic differential equation representations. A more general family of non-Gaussian …

    cambridge Repository record for Non-Gaussian Stochastic Process Priors for Learning (opens in a new tab)

  5. Modern Bayesian Object Tracking: Challenges and Solutions

    … tracking problems by exploring modelling and inference strategies to speed up and scale the sampling structures. A highlight of this thesis is the application of Rao-Blackwellisation strategies for different inference and tracking tasks, which could be a good case study for learning the …

    cambridge Repository record for Modern Bayesian Object Tracking: Challenges and Solutions (opens in a new tab)