Skip to main content

Publications

If you would like a copy of any of the publications listed here, which are not available to be downloaded, then please send me an email and I'll endeavour to supply one.

Recent Reports

  1. L. J. Rendell, A. M. Johansen, A. Lee and N. Whiteley. Global consensus Monte Carlo. ArXiv mathematics e-print 1807.09288 [arxiv]
  2. A. Finke, A. Doucet, and A. M. Johansen. Limit theorems for sequential MCMC methods. ArXiv mathematics e-print 1807.01057 [arxiv]
  3. J. Koskela, P. Jenkins, A. M. Johansen, and D. Spanò. Asymptotic genealogies of interacting particle systems with an application to sequential Monte Carlo. ArXiv mathematics e-print 1804.01811 [arxiv]
  4. A. Finke, A. Doucet and A. M. Johansen. On embedded hidden Markov models and particle Markov chain Monte Carlo methods. ArXiv mathematics preprint 1610.08962. [arxiv]
  5. M. Pollock, P. Fearnhead, A. M. Johansen and G. O. Roberts. The Scalable Langevin Exact Algorithm: Bayesian Inference for Big data. ArXiv mathematics preprint 1609.03436. [arxiv]

Journal Articles and Preprints

  1. M. Thorpe and A. M. Johansen. Pointwise Convergence in Probability of General Smoothing Splines. Annals of the Institute of Statistical Mathematics 70(4):717--744, 2018. [journal|arxiv]
  2. P. Guarniero, A. M. Johansen and A. Lee. The Iterated Auxiliary Particle Filter. Journal of the American Statistical Association 112(520):1636-1647, 2017 [journal|arxiv]
  3. Faye M. Nixon, Thomas R. Honnor, Nicholas I. Clarke, Georgina P. Starling, Alison J. Beckett, Adam M. Johansen, Julia A. Brettschneider, Ian A. Prior, Stephen J. Royle. Microtubule organization within mitotic spindles revealed by serial block face scanning EM and image analysis. Journal of Cell Science 130:1845-1855, 2017 [journal]
  4. F. Lindsten, A. M. Johansen, C. Naesseth, B. Kirkpatrick, T. Schön, J. A. D. Aston, and A. Bouchard-Côté. Divide and conquer with sequential Monte Carlo. Journal of Computational and Graphical Statistics 26(2):445–458, 2017. [journal website|arxiv]
  5. R. G. Everitt, A. M. Johansen, E. Rowing, and M. Evdemon-Hogan. Bayesian model selection with un-normalised likelihoods. Statistics and Computing 27(2):403-422, 2017. [journal|arxiv].
  6. M. Thorpe and A. M. Johansen. Convergence and Rates for Fixed-Interval Multiple-Track Smoothing Using k-Means Type Optimization. Electronic Journal of Statistics 10(2):3693-3722, 2016. [journal|arxiv]
  7. Y. Zhou, A. M. Johansen and J. A. D. Aston, Towards Automatic Model Comparison: An Adaptive Sequential Monte Carlo Approach. Journal of Computational and Graphical Statistics, 25(3):701-726, 2016. [journal|arxiv]
  8. M. Pollock, A. M. Johansen and G. O. Roberts, On Exact and $\varepsilon$-strong Simulation of (Jump) Diffusions. Bernoulli, 22(2):794--856, 2016. [pdf|journal website|arxiv].
  9. M. Thorpe, F. Theil, A. M. Johansen, and N. Cade. Convergence of the k-means minimization problem using $\Gamma$-convergence. SIAM Journal on Applied Mathematics, 75(6):2444-2474, 2015. [journal||arxiv]
  10. N. Barry, A. Pitto-Barry, J. Tran, S. Spencer, A. M. Johansen, A. M. Sanchez, A. P. Dove, R. K. O'Reilly, R. Deeth, R. Beanland, P. J. Sadler. Osmium Atoms and Os2 Molecules Move Faster on Selenium-doped Compared to Sulfur-doped Boronic Graphenic Surfaces, Chemistry of Materials, 27(14):5100-5106, 2015. [ journal ]
  11. A. Finke, A. M. Johansen and D. Spanò, Static-parameter estimation in piecewise deterministic processes using particle Gibbs samplers. Annals of the Institute of Statistical Mathematics (Tokyo), 66(3):577–609, 2014. [Journal Version | Preprint also available as CRiSM Working Paper 14-03]
  12. C. F. H. Nam, J. A. D. Aston and A. M. Johansen. Parallel Sequential Monte Carlo Samplers and Estimation of the Number of States in a Hidden Markov Model. Annals of the Institute of Statistical Mathematics (Tokyo), 66(3):553–575, 2014. [Journal version | CRiSM Working Paper 12-23 (earlier version)]
  13. A. Sorrentino, A. M. Johansen, J. A. D. Aston, T. E. Nichols and W. S. Kendall. Dynamic filtering of Static Dipoles in MagnetoEncephaloGraphy. Annals of Applied Statistics, 7(2):955-988, 2013. [Journal Version | arxiv]
  14. F. J. Rubio and A. M. Johansen, A simple approach to maximum intractable likelihood estimation. Electronic Journal of Statistics, 7:1632--1654, 2013. [Journal version]
  15. Y. Zhou, J. A. D. Aston and A. M. Johansen, Bayesian Model Comparison for Compartmental Models with Applications in Positron Emission Tomography. Journal of Applied Statistics, 40(5):993-1016, 2013. [Journal version]
  16. C. F. H. Nam, J. A. D. Aston and A. M. Johansen, Quantifying the Uncertainty in Change Points. Journal of Time Series Analysis, 33(5):807--823, 2012 [Abstract|pdf]
  17. N. Whiteley, A. M. Johansen, and S. Godsill. Monte Carlo filtering of piecewise-deterministic processes. Journal of Computational and Graphical Statistics, 20(1):119-139, 2011. [Journal Version|.pdf]
  18. X. Didelot, R. G. Everitt, A. M. Johansen, and D. J. Lawson. Likelihood-free estimation of model evidence. Bayesian Analysis, 6(1):49-74, March 2011. [.pdf]
  19. A. Doucet, A. M. Johansen, and V. B. Tadić. On solving integral equations using Markov Chain Monte Carlo. Applied Mathematics and Computation, 216:2869-2880, 2010. [Journal Version|.pdf ]
  20. A. M. Johansen. SMCTC: Sequential Monte Carlo in C++. Journal of Statistical Software, 30(6):1-41, April 2009. [Journal Version|Draft with line numbers for source code.]
  21. A. M. Johansen and A. Doucet. A note on the auxiliary particle filter. Statistics and Probability Letters, 78(12):1498-1504, September 2008. [.djvu | http | .ps | .pdf ]
  22. A. M. Johansen, A. Doucet, and M. Davy. Particle methods for maximum likelihood parameter estimation in latent variable models. Statistics and Computing, 18(1):47-57, March 2008. [.pdf ]
  23. J. R. James, S. S. White, R. W. Clarke, A. M. Johansen, et al. Single molecule-level analysis of the subunit composition of the T-cell receptor on live T cells. Proceedings of the National Academy of Science, USA, 104(45):17662-17667, November 2007. [http ]
  24. G. W. Peters, A. M. Johansen, and A. Doucet. Simulation of the annual loss distribution in operational risk via Panjer recursions and Volterra integral equations for value at risk and expected shortfall estimation. Journal of Operational Risk, 2(3):29-58, Fall 2007. [ http ]
  25. A. M. Johansen, S. S. Singh, A. Doucet, and B.-N. Vo. Convergence of the SMC implementation of the PHD filter. Methodology and Computing in Applied Probability, 8(2):265-291, June 2006. [http | .pdf ]
  26. Jodie Smith, David Onley, Caroline Garey, Stuart Crowther, Nicholas Cahir, Adam Johansen, Sianie Painter, Grant Harradence, Ricardo Davis, and Peter Swarbrick. Determination of ANA specificity using the UltraPlexTM platform. Annals of the New York Academy of Sciences, 1050:286-294, 2005.
  27. C. J. Edgcombe and A. M. Johansen. Current-voltage characteristics of nonplanar cold field emitters. Journal of Vacuum Science Technology B, 21(4):1519-1523, July 2003. [.djvu | .html | .ps | .pdf ]

Book Chapters

  1. A. M. Johansen. Markov chain Monte Carlo. In SAGE Encyclopedia of Educational Research, Measurement and Evaluation, February 2018. SAGE.
  2. J. A. D. Aston and A. M. Johansen. Bayesian Inference on the Brain: Bayesian Solutions to Selected Problems in Neuroimaging. In Current Trends in Bayesian Methodology, May 2015. CRC Press.
  3. N. Whiteley and A. M. Johansen. Recent Developments in Auxiliary Particle Filtering. In Bayesian Time Series Models, 2011, Barber, Cemgil and Chiappa (eds). Cambridge University Press, [pdf]
  4. A. Doucet and A. M. Johansen. A Tutorial on Particle filtering and smoothing: Fiteen years later. In The Oxford Handbook of Nonlinear Filtering, D. Crisan and B. Rozovsky (eds.). Oxford University Press, 2011. [pdf]
  5. A. M. Johansen. Monte Carlo methods. In E. Baker, P. Peterson and B. McGraw, editors, International Encyclopaedia of Education. Elsevier, 3rd edition, 2010.
  6. A. M. Johansen. Markov Chain Monte Carlo. In E. Baker, P. Peterson and B. McGraw, editors, International Encyclopaedia of Education. Elsevier, 3rd edition, 2010.
  7. A. M. Johansen. Markov Chains. In B. Wah, editor, Encyclopaedia of Computer Science and Engineering. John Wiley and Sons, Inc., 111 River Street, MS 8-02, Hoboken, NJ 07030-5774, Volume 4:1800-1808, January 2009. [ http | Wiley Encyclopedia of Computer Science and Engineering at Amazon.co.uk]

Conference Proceedings

  1. A. M. Johansen. On Blocks, Tempering and Particle MCMC for Systems Identification. In Proceedings of 17th IFAC Symposium on System Identification, October 19-21, 2015, p.969-974, Beijing International Convention Center, Beijing, China. [.pdf | proceedings]
  2. Y. Zhou, A. M. Johansen and J. A. D. Aston, Bayesian model comparison via path-sampling sequential Monte Carlo. In Proceedings of IEEE Workshop on Statistical Signal Processing, 2012. [Abstract|pdf]
  3. A. M. Johansen, N. Whiteley and A. Doucet. Exact approximation of Rao-Blackwellised particle filters. In Proceedings of 16th IFAC Symposium on Systems Identification. Brussels, July 2012. [pdf]
  4. A. M. Johansen and N. Whiteley. A modern perspective on auxiliary particle filters. In Proceedings of Workshop on Inference and Estimation in Probabilistic Time Series Models. Isaac Newton Institute, June 2008. [.pdf ]
  5. N. Whiteley, A. M. Johansen, and S. Godsill. Efficient Monte Carlo filtering for discretely observed jumping processes. In Proceedings of IEEE Statistical Signal Processing Workshop, pages 89-93, Madison, WI, USA, August 26th-29th 2007. [ .djvu | .ps | .pdf ]
  6. A. M. Johansen, P. Del Moral, and A. Doucet. Sequential Monte Carlo samplers for rare events. In Proceedings of the 6th International Workshop on Rare Event Simulation, pages 256-267, Bamberg, Germany, October 2006. [.djvu | .ps | .pdf ]
  7. A. M. Johansen, A. Doucet, and M. Davy. Maximum likelihood parameter estimation for latent models using sequential Monte Carlo. In Proceedings of ICASSP, volume III, pages 640-643, May 2006. [.djvu | .ps | .pdf ]

Discussion Contributions and Comments

  1. A. Finke, A. Hetland, A. Lee and A. M. Johansen. Discussion of "Sequential Quasi-Monte Carlo Methods" by Gerber and Chopin Journal of the Royal Statistical Society B, 77(3):557–558, 2015.
  2. M. Pollock, A. M. Johansen, K. Łatuszýnski and G. O. Roberts. Discussion of "Sequential Quasi-Monte Carlo Methods" by Gerber and Chopin. Journal of the Royal Statistical Society B, 77(3):556–557, 2015.
  3. A. Doucet, P. Jacob and A. M. Johansen, Discussion of "Riemannian Manifold Langevin and Hamiltonian Monte Carlo Methods" by Girolami and Calderhead. Journal of the Royal Statistical Society B, 73(2):162 April 2011.
  4. A. M. Johansen and J. A. D. Aston, Discussion of "Particle Markov chain Monte Carlo methods" by Andrieu, Doucet and Holenstein. Journal of the Royal Statistical Society B, 72(3):326-327, June 2010.
  5. A. M. Johansen, Discussion of "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations" by Rue, Martino, and Chopin. Journal of the Royal Statistical Society B, 71(2):358, April 2009.

Older Technical Reports and Miscellanea

  1. A. M. Johansen and A. Doucet. Auxiliary variable sequential Monte Carlo methods. Research Report 07:09, University of Bristol, Department of Mathematics - Statistics Group, University Walk, Bristol, BS8 1TW, UK, July 2007. [.djvu | .ps | .pdf ]
    A substantially shorter version focusing on particle filtering subsequently appeared in Statistics and Probability Letters.
  2. A. M. Johansen. Some Non-Standard Sequential Monte Carlo Methods With Applications. PhD thesis, University of Cambridge Department of Engineering, 2006. [.pdf ]
  3. Adam Michael Johansen and W. J. Fitzgerald. Unsupervised generalised Gaussian mixture model classification using the EM algorithm. Technical Report CUED/F-INFENG/TR-455, University of Cambridge, Department of Engineering, Cambridge University Engineering Department, Trumpington Street, Cambridge, CB2 1PZ, May 2003.


Indexing and Agglomeration Services and Eprint Servers


Google Scholar EconPapers MathSciNet Research Gate Scientific Commons arXiv