Article-Journal

Partial state-feedback reduced-order switching predictive models for next-generation optical lithography systems
This paper presents a partial state-feedback reduced-order switching predictive model designed to support the next-generation …
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A Factor Graph Approach to Variational Sparse Gaussian Processes
A Variational Sparse Gaussian Process (VSGP) is a sophisticated nonparametric probabilistic model that has gained significant …
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Factor graph-based online Bayesian identification and component evaluation for multivariate autoregressive exogenous input models
We present a Forney-style factor graph representation for the class of multivariate autoregressive models with exogenous inputs, and propose an online Bayesian parameter-identification procedure based on message-passing within this graph.
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Multiple variational Kalman-GRU for ship trajectory prediction with uncertainty
Accurate prediction of ship trajectories is crucial for ensuring safe and efficient navigation. However, predicting ship trajectories …
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GraphPPL.jl: A Probabilistic Programming Language for Graphical Models
This paper presents GraphPPL.jl, a novel probabilistic programming language designed for graphical models. GraphPPL.jl uniquely …
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Bayesian inference of collision avoidance intent during ship encounters
Ship collision accidents frequently cause casualties and significant property losses. These collisions mainly occur by incorrectly …
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Information-seeking polynomial NARX model-predictive control through expected free energy minimization
We propose an adaptive model-predictive controller that balances driving the system to a goal state and seeking system observations …
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Principled Pruning of Bayesian Neural Networks through Variational Free Energy Minimization
Bayesian model reduction provides an efficient approach for comparing the performance of all nested sub-models of a model, without …
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Automating model comparison in factor graphs
Bayesian state and parameter estimation are automated effectively in a variety of probabilistic programming languages. The process of …
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Realising Synthetic Active Inference Agents, Part II: Variational Message Updates
The free energy principle (FEP) describes (biological) agents as minimizing a variational free energy (FE) with respect to a generative …
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