Graphical model inference: Sequential Monte Carlo meets deterministic approximations

NeurIPS 2018 Fredrik LindstenJouni HelskeMatti Vihola

Approximate inference in probabilistic graphical models (PGMs) can be grouped into deterministic methods and Monte-Carlo-based methods. The former can often provide accurate and rapid inferences, but are typically associated with biases that are hard to quantify... (read more)

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