| The boomerang sampler J Bierkens, S Grazzi, K Kamatani, G Roberts International conference on machine learning, 908-918, 2020 | 49 | 2020 |
| A piecewise deterministic Monte Carlo method for diffusion bridges J Bierkens, S Grazzi, F van der Meulen, M Schauer Statistics and Computing 31 (3), 37, 2021 | 21 | 2021 |
| Sticky PDMP samplers for sparse and local inference problems J Bierkens, S Grazzi, F Meulen, M Schauer Statistics and Computing 33 (1), 8, 2023 | 14 | 2023 |
| Methods and applications of PDMP samplers with boundary conditions J Bierkens, S Grazzi, G Roberts, M Schauer arXiv preprint arXiv:2303.08023, 2023 | 4 | 2023 |
| Bayesian inference for SDE models: a case study for an excitable stochastic-dynamical model S Grazzi, F van der Meulen, M Mider, M Schauer NextJournal, 2020 | 2 | 2020 |
| Design and applications of Monte Carlo methods based on piecewise deterministic Markov processes S Grazzi | 1 | 2023 |
| mschauer/PointProcessInference. jl: v0. 2.2 M Schauer, F Van Der Meulen, S Gugushvili Zenodo, 2020 | 1 | 2020 |
| Stochastic Gradient Piecewise Deterministic Monte Carlo Samplers P Fearnhead, S Grazzi, C Nemeth, GO Roberts arXiv preprint arXiv:2406.19051, 2024 | | 2024 |
