# About Me

- ACEMS Research Fellow (Jan. 2019 – Present) — UNSW Sydney
- ACEMS Research Fellow (Aug. 2018 – Jan. 2019) [Short-Term Contract] — The University of Queensland
- PhD Candidate in Statistics (2015-2018) — The University of Queensland.
- Advisor: Professor Dirk Kroese | Thesis:
*Advances in Monte Carlo Methodology*

- Advisor: Professor Dirk Kroese | Thesis:

For more details, see my recent CV.

# Research Interests

My research, generally speaking, lies at the intersection of computational statistics and probabilistic machine learning. I am broadly interested in these fields, but more specifically am interested in novel methodological methods and theory relating

- Inference Algorithms (e.g., Markov Chain Monte Carlo, Sequential Monte Carlo, and Variational Methods)
- Kernelized Stein Discrepencies
- Deep Generative Models (e.g., Normalizing Flows and Variational Autoencoders)
- Variance Reduction and Unbiased Estimation in Monte Carlo Simulation

# Research Output

### Pipeline

Hodgkinson, L., **Salomone, R.**, and Roosta, F. (2020), *The reproducing Stein kernel approach for post-hoc corrected sampling. arXiv: 2001.09266*

**Salomone, R.**, South, L.F., Drovandi, C.C., and Kroese, D.P. (2018),* Unbiased and Consistent Nested Sampling via Sequential Monte Carlo*. arXiv:1805.03924

### Publications

**Salomone R.**, Quiroz, M., Kohn, R., Villani, M., and Tran, M.N. (2020), *Spectral Subsampling MCMC for **Stationary Time Series. * Proceedings of the International Conference on Machine Learning (ICML) 2020*. * [Read Online]

Hodgkinson, L.,** Salomone,R.**, and Roosta, F. (2020), *Implicit Langevin Algorithms for Sampling From Log-concave Densities.* Accepted at the Journal of Machine Learning Research (JMLR) , with minor revision. arxiv:1903.12322

Botev, Z.I., **Salomone, R.**, Mackinlay, D. (2019), *Fast and accurate computation of the distribution of sums of dependent log-normals*, Annals of Operations Research 280 (1), 19-46. [Read Online]

Laub, P.J.,** Salomone**, **R.**, Botev, Z.I. (2019), *Monte Carlo estimation of the density of the sum of dependent random variables*, Mathematics and Computers in Simulation 161, 23-31.

**Salomone, R.,** Vaisman, R., and Kroese, D.P. (2016). *Estimating the Number of Vertices in Convex Polytopes*. Proceedings of the Annual International Conference on Operations Research and Statistics, ORS 2016. [Read Online]

# Selected Presentations

- A Tutorial on Reproducing Stein Kernels
- Slides and Jupyter Notebook for my three-hour workshop on Automatic Differentiation.