22 citations · 23 across the 5 of their papers we have counts for
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stat.ML2021★ 22 cited
Efficient Learning of the Parameters of Non-Linear Models using Differentiable Resampling in Particle Filters
Conor Rosato, Vincent Beraud, Paul Horridge +2
It has been widely documented that the sampling and resampling steps in particle filters cannot be differentiated. The {\itshape reparameterisation trick} was introduced to allow t…
stat.CO2021★ 1 cited
The No-U-Turn Sampler as a Proposal Distribution in a Sequential Monte Carlo Sampler with a Near-Optimal L-Kernel
Lee Devlin, Paul Horridge, Peter L. Green +1
Markov Chain Monte Carlo (MCMC) is a powerful method for drawing samples from non-standard probability distributions and is utilized across many fields and disciplines. Methods suc…