Wilson (Ye) Chen is a Senior Lecturer. He received a PhD in Financial Econometrics from the University of Sydney. Prior to returning to the University of Sydney as a Lecturer in April 2020, he was a post-doctoral fellow at the University of Technology Sydney, and then an Assistant Professor at the Institute of Statistical Mathematics in Japan. Wilson's current research aims to develop efficient computational methods for Bayesian inference, as well as statistical tools for the analysis of financial time series data.
| Project title | Research student |
|---|---|
| Optimization on the space of probability measures | Peiwen JIANG |
| Bayesian Neural Networks for Volatility Dynamics Detection | Wen PENG |
| Actuarial Studies with machine learning and statistical modelling | Yuning ZHANG |
Publications
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Journals
- Chen, Y., Peters, G., Gerlach, R., Sisson, S. (2022). Dynamic quantile function models. Quantitative Finance, 22(9), 1665-1691. [More Information]
- Riabiz, M., Chen, W., Cockayne, J., Swietach, P., Niederer, S., MacKey, L., Oates, C. (2022). Optimal thinning of MCMC output. Journal of the Royal Statistical Society Series B, 84(4), 1059-1081. [More Information]
- Chen, W., Gerlach, R. (2021). Semiparametric GARCH via Bayesian Model Averaging. Journal of Business and Economic Statistics, 39(2), 437-452. [More Information]
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Conferences
- Chen, W., Barp, A., Briol, F., Gorham, J., Girolami, M., MacKey, L., Oates, C. (2019). Stein point Markov chain Monte Carlo. 36th International Conference on Machine Learning (ICML 2019), : SPIE.
- Chen, W., MacKey, L., Gorham, J., Briol, F., Oates, C. (2018). Stein points. 35th International Conference on Machine Learning (ICML 2018), Stockholm: International Machine Learning Society.
- Briol, F., Oates, C., Cockayne, J., Chen, W., Girolami, M. (2017). On the sampling problem for Kernel quadrature. 34th International Conference on Machine Learning (ICML 2017), Sydney, Australia: International Machine Learning Society.
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2022
- Chen, Y., Peters, G., Gerlach, R., Sisson, S. (2022). Dynamic quantile function models. Quantitative Finance, 22(9), 1665-1691. [More Information]
- Riabiz, M., Chen, W., Cockayne, J., Swietach, P., Niederer, S., MacKey, L., Oates, C. (2022). Optimal thinning of MCMC output. Journal of the Royal Statistical Society Series B, 84(4), 1059-1081. [More Information]
2021
- Chen, W., Gerlach, R. (2021). Semiparametric GARCH via Bayesian Model Averaging. Journal of Business and Economic Statistics, 39(2), 437-452. [More Information]
2020
- Chen, W., Wand, M. (2020). Factor graph fragmentization of expectation propagation. Journal of the Korean Statistical Society, 49(3), 722-756. [More Information]
2019
- Chen, W., Barp, A., Briol, F., Gorham, J., Girolami, M., MacKey, L., Oates, C. (2019). Stein point Markov chain Monte Carlo. 36th International Conference on Machine Learning (ICML 2019), : SPIE.
2018
- Chen, W., MacKey, L., Gorham, J., Briol, F., Oates, C. (2018). Stein points. 35th International Conference on Machine Learning (ICML 2018), Stockholm: International Machine Learning Society.
2017
- Briol, F., Oates, C., Cockayne, J., Chen, W., Girolami, M. (2017). On the sampling problem for Kernel quadrature. 34th International Conference on Machine Learning (ICML 2017), Sydney, Australia: International Machine Learning Society.
2016
- Peters, G., Chen, Y., Gerlach, R. (2016). Estimating Quantile Families of Loss Distributions for Non-Life Insurance Modelling via L-Moments. Risks, 4(14), 1-41. [More Information]