Pierre E. Jacob
- Sequential Monte Carlo methods
- Sequential Inference, Modularization
- High Dimensional, Non-linear State Space models
- Parallel Computing in Monte Carlo algorithms
Ph.D. in Statistics, Université Paris-Dauphine, September 2012
M.Sc. in Statistics, Université Paris-Dauphine, September 2009
ENSAE ParisTech ("grande école" 3 years program in Economics, Finance and Statistics), September 2009
July 2015 - now, Assistant Professor, Harvard University.
October 2013 - June 2015, Post-doctoral fellow, Department of Statistics, University of Oxford.
October 2012 - September 2013, Post-doctoral fellow, Department of Statistics and Applied probability, National University of Singapore
Jacob, P.E., Thiery, A.H. (2015).
On non-negative unbiased estimators,
Annals of Statistics (43 (2), 769-784)
Jacob, P.E., Murray, L.M., Rubenthaler, S. (2015).
Path storage in the particle filter,
Statistics and Computing (25(2), 487-496)
Jacob, P.E., Ryder, R. (2014)
The Wang-Landau algorithm reaches the Flat Histogram criterion in finite time,
Annals of Applied Probability (24 (1), 34-53)
Chopin, N., Jacob, P.E., Papaspiliopoulos, O. (2013).
SMC2: an efficient algorithm for sequential analysis of state-space models,
Journal of the Royal Statistical Society: Series B (75 (3), 397-426)