… We introduce a stochastic version of the nonreversible, rejection-free Bouncy Particle Sampler
(BPS), a Markov process whose sample trajectories are piecewise linear, to efficiently sam…

… , a general algorithm based on a guided random walk, a partial refreshment of direction …
bounce in the bouncy particle sampler, and we show that the discrete bouncy particle sampler …

… method will be henceforth referred to as the bouncy particle sampler (BPS). This algorithm
and … is constant for a given v, we sample τ [r] by simulating an exponential random variable. …

… of iid random variables (Ei,Fi,Gi)i∈N∗ on the same probability space ( ,F,P), where for all i
∈ N∗ , Ei,Fi are exponential random variables with parameter 1, Gi is a random variable with …

… We focus here on the Bouncy Particle Sampler … random walk Metropolis algorithm. We
change variables to obtain a transformed target satisfying our conditions and use BPS to sample …

… alleviate this cost, and allow for efficient sampling within BNNs. We propose a simplified
version of the Stochastic Bouncy Particle Sampler, making it suitable to perform inference on …

… the performance of even the most advanced particle filters in higher dimensions is avoided.
… the discrete bouncy particle sampler, which is based on constructing a guided random walk …

… When using a Bouncy Particle Sampler, we need to tune … sample which exhibits random
walk characteristics, which we wish to avoid. This means that whilst the Bouncy Particle Sampler …

The bouncy particle sampler is a Markov chain Monte Carlo method … particle explores the
state space of interest by evolving according to a linear dynamics which is altered by bouncing …

… draw samples from target distribution efficiently. We generalize bouncy particle sampler in
… In BPS, the transition dynamic at event time is deterministic, but in GBPS, it is random. With …