Particle methods for change detection, system identification, and control

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How researchers see this paper

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System identification of nonlinear state-space models (2011, methodology): “The survey paper [3] is one of the earliest papers to note the possiblility of EM-based methods employing particle smoothing methods.”
Robot navigation in dense human crowds: Statistical models and experimental studies of human–robot cooperation (2015, neutral): “split(line) end_time = float(line_splitted[1]) track_id = int(line_splitted[2]) path_info = line_splitted[3].”
An Overview of Existing Methods and Recent Advances in Sequential Monte Carlo (2007, methodology): “This approximation has been derived by [87], [88], [89], [90] using different arguments (see also [89], [83], [91] for alternative proposals).”
Multimodal fusion for multimedia analysis: a survey (2010, neutral): “Particle filters are a set of sophisticated simulation-based methods, which are often used to estimate the state distribution of the non-linear and non-Gaussian state-space model [6].”