1. Andrieu, C., Livingstone, S.:. Peskun–Tierney ordering for Markov chain and process Monte Carlo: beyond the reversible scenario (2019). arXiv: 1906.06197
2. Bento, J., Ibrahimi, M., Montanari, A.: Learning networks of stochastic differential equations (2010). arXiv: 1011.0415
3. Bierkens, J., Fearnhead, P., Roberts, G.: The Zig-Zag process and super-efficient sampling for Bayesian analysis of big data. Ann. Stat. 47(3), 1288–1320 (2019)
4. Bierkens, J., Grazzi, S., Kamatani, K., Roberts, G.: The boomerang sampler. In: International Conference on Machine Learning, PMLR, pp. 908–918 (2020)
5. Bierkens, J., Grazzi, S., van der Meulen, F., Schauer, M.: A piecewise deterministic Monte Carlo method for diffusion bridges. Stat. Comput. 31(3), 1–21 (2021)