3 citations · 3 across the 4 of their papers we have counts for
4 papers
Improved Disease Outbreak Detection from Out-of-sequence measurements Using Markov-switching Fixed-lag Particle Filters
Conor Rosato, Joshua Murphy, Siân E. Jenkins +7
Particle filters (PFs) have become an essential tool for disease surveillance, as they can estimate hidden epidemic states in nonlinear and non-Gaussian models. In epidemic modelli…
Enhanced SMC: Leveraging Gradient Information from Differentiable Particle Filters Within Langevin Proposals
Conor Rosato, Joshua Murphy, Alessandro Varsi +2
Sequential Monte Carlo Squared (SMC) is a Bayesian method which can infer the states and parameters of non-linear, non-Gaussian state-space models. The standard random-walk pro…
An SMC Algorithm on Distributed Memory with an Approx. Optimal L-Kernel
Conor Rosato, Alessandro Varsi, Joshua Murphy +1
Calibrating statistical models using Bayesian inference often requires both accurate and timely estimates of parameters of interest. Particle Markov Chain Monte Carlo (p-MCMC) and…
A Single SMC Sampler on MPI that Outperforms a Single MCMC Sampler
Alessandro Varsi, Lykourgos Kekempanos, Jeyarajan Thiyagalingam +1
Markov Chain Monte Carlo (MCMC) is a well-established family of algorithms which are primarily used in Bayesian statistics to sample from a target distribution when direct sampling…