Skip to main content Skip to navigation

Dr Paul Jenkins

I am an Associate Professor of Data Science in Statistics and Computer Science, and a Fellow of the Alan Turing Institute, with interests in Monte Carlo methods, inference from stochastic processes, mathematical population genetics, machine learning for genomics. I am a member of the Warwick Machine Learning group.

Teaching

ST208: Mathematical Methods

ST340: Programming for Data Science

ST343: Topics in Data Science

ST419: Advanced Topics in Data Science

APTS Computer Intensive Statistics

Preprints

Mider, M., Jenkins, P. A., Pollock, M., Roberts, G. O., and Sørensen, M. Simulating bridges using confluent diffusions.
[ arXiv]

Jenkins, P. A. Exact simulation of the sample paths of a diffusion with a finite entrance boundary.
[ arXiv ]

Publications

Koskela, J., Jenkins, P. A., Johansen, A. M., and Spanò, D. Asymptotic genealogies of interacting particle systems with an application to sequential Monte Carlo. Annals of Statistics, to appear.
[ arXiv ]

Koskela, J., Spanò, D., and Jenkins, P. A. (2019). Consistency of Bayesian nonparametric inference for discretely observed jump diffusions. Bernoulli, 25 (3): 2183–2205.
[ Abstract ] [ arXiv ]

Favaro, S., Feng, S., and Jenkins, P. A. (2019). Bayesian nonparametric analysis of Kingman's coalescent. Annales de l'Institut Henri Poincaré (B) Probability and Statistics, 55 (2): 1087–1115.
[ Abstract ] [ arXiv ]

Chan, J., Perrone, V., Spence, J. P., Jenkins, P. A., Mathieson, S., and Song, Y. S. (2018). A likelihood-free inference framework for population genetic data using exchangeable neural networks. Advances in Neural Information Processing Systems 31:8594–8605.
[ Abstract & PDF ] [ arXiv ] [ bioRxiv ]

Griffiths, R., Jenkins, P. A., and Spanò, D. (2018). Wright-Fisher diffusion bridges. Theoretical Population Biology, 122: 67–77.
[ Abstract ] [ arXiv ]

Koskela, J., Jenkins, P. A., and Spanò, D. (2018). Bayesian non-parametric inference for Λ-coalescents: consistency and a parametric method. Bernoulli, 24 (3): 2122–2153.
[ Abstract ] [ arXiv ]

Koskela, J., Jenkins, P. A., and Spanò, D. (2018). Inference and rare event simulation for stopped Markov processes via reverse-time sequential Monte Carlo. Statistics & Computing, 28 (1): 131–144.
[ Abstract ] [ arXiv ]

Perrone, V., Jenkins, P. A., Spanò, D., and Teh, Y. W. (2017). Poisson random fields for dynamic feature models. Journal of Machine Learning Research, 18 (127): 1–45.
[ Abstract & PDF ] [ arXiv ]

Griffin, A., Jenkins, P. A., Roberts, G. O., and Spencer, S. E. F. (2017). Simulation from quasi-stationary distributions on reducible state spaces. Advances in Applied Probability, 49 (3): 960–980.
[ Abstract ] [ arXiv ]

Jenkins, P. A., and Spanò, D. (2017). Exact simulation of the Wright-Fisher diffusion. Annals of Applied Probability, 27 (3): 1478–1509.
[ Abstract ] [ arXiv ] [ CRiSM Working Paper 14-27 (an earlier version) ]

Griffiths, R. C., Jenkins, P. A., and Lessard, S. (2016). A coalescent dual process for a Wright-Fisher diffusion with recombination and its application to haplotype partitioning. Theoretical Population Biology, 112: 126–138.
[ Abstract ] [ arXiv ] [ Oberwolfach report ]

Dialdestoro, K., Sibbesen, J. A., Maretty, L., Raghwani, J., Gall, A., Kellam, P., Pybus, O. G., Hein, J., and Jenkins, P. A. (2016). Coalescent inference using serially sampled, high-throughput sequencing data from intra-host HIV infection. Genetics, 202 (4): 1449–1472.
[ Abstract ] [ bioRxiv ]

Koskela, J., Jenkins, P., and Spanò, D. (2015). Computational inference beyond Kingman's coalescent. Journal of Applied Probability, 52 (2): 519–537.
[ Abstract ] [ arXiv ]

Jenkins, P. A., Fearnhead, P., and Song, Y. S. (2015). Tractable diffusion and coalescent processes for weakly correlated loci. Electronic Journal of Probability, 20 (58): 1-26. 
[ Abstract & PDF ] [ arXiv ]

Jenkins, P. A., Mueller, J.W, and Song, Y. S. (2014). General triallelic frequency spectrum under demographic models with variable population size. Genetics, 196 (1): 295–311.
[ Abstract ] [ arXiv ]

Chan, A. H., Jenkins, P. A., and Song, Y. S. (2012). Genome-wide fine-scale recombination rate variation in Drosophila melanogaster. PLoS Genetics, 8 (12): e1003090.
[ Abstract & PDF ] [ Software ]

Jenkins, P. A., Song, Y. S., and Brem, R. B. (2012). Genealogy-based methods for inference of historical recombination and gene flow and their application in Saccharomyces cerevisiae. PLoS ONE, 7 (11): e46947.
[ Abstract & PDF ]

Jenkins, P. A. and Song, Y. S. (2012). Padé approximants and exact two-locus sampling distributions. Annals of Applied Probability, 22 (2): 576–607.
(Technical Report #793, Department of Statistics, University of California, Berkeley, 2010.)
[ Abstract ] [ arXiv ] [ Tech Report Version ]

Jenkins, P. A. (2012). Stopping-time resampling and population genetic inference under coalescent models. Statistical Applications in Genetics and Molecular Biology, 11 (1): Article 9.
[ Abstract ] [ PDF ]

Jenkins, P. A. and Song, Y. S. (2011). The effect of recurrent mutation on the frequency spectrum of a segregating site and the age of an allele. Theoretical Population Biology, 80 (2): 158–173.
[ Abstract ] [ Preprint ]

Jenkins, P. A. and Griffiths, R. C. (2011). Inference from samples of DNA sequences using a two-locus model. Journal of Computational Biology, 18 (1): 109–127.
[ Abstract ] [ PDF ]

Jenkins, P. A. and Song, Y. S. (2010). An asymptotic sampling formula for the coalescent with recombination. Annals of Applied Probability, 20 (3): 1005–1028.
(Technical Report #775, Department of Statistics, University of California, Berkeley, 2009.)
[ Abstract ] [ arXiv ] [ Tech Report Version ]

Jenkins, P. A. and Song, Y. S. (2009). Closed-form two-locus sampling distributions: accuracy and universality. Genetics, 183 (3): 1087–1103.
[ Abstract ] [ PDF ] [ Software ]

Griffiths, R. C., Jenkins, P. A., and Song, Y. S. (2008). Importance sampling and the two-locus model with subdivided population structure. Advances in Applied Probability, 40 (2): 473–500.
[ Abstract ] [ Preprint ]

Jenkins, P., Lyngsø, R., and Hein, J. (2006). How many transcripts does it take to reconstruct the splice graph? In: Proceedings of the Workshop on Algorithms in Bioinformatics, Lecture Notes in Computer Science vol. 4175, pp. 103–114.
[ Abstract ] [ PDF ] [ Supplementary material ]

Thesis

Importance sampling on the coalescent with recombination. University of Oxford, 2008.
[ Abstract ] [ PDF ]

photo_pj.png

Contact:

Dr Paul Jenkins
Dept of Statistics
University of Warwick
Coventry, CV4 7AL
United Kingdom
Voice:

024 7657 4856

Email:

p dot jenkins at warwick dot ac dot uk

Office:

MSB 2.20.

Term 3 office hours:
Thu 09:30 - 10:30 (week 1 only),
Tue 09:30 - 10:30 (weeks 2-10),
Wed 10:30 - 11:30 (weeks 2-10).