9 citations · 12 across the 11 of their papers we have counts for
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stat.CO2019
On the use of approximate Bayesian computation Markov chain Monte Carlo with inflated tolerance and post-correction
Matti Vihola, Jordan Franks
Approximate Bayesian computation allows for inference of complicated probabilistic models with intractable likelihoods using model simulations. The Markov chain Monte Carlo impleme…
stat.ML2019★ 9 cited
Graphical model inference: Sequential Monte Carlo meets deterministic approximations
Fredrik Lindsten, Jouni Helske, Matti 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 ra…