Publications (Statistical Theory and Methodology) | Department of Statistics

Publications

Lomelí, M., Favaro, S. and Teh, Y. (2016) “A marginal sampler for σ-stable Poisson–Kingman mixture models”, Journal of Computational and Graphical Statistics, 26(1), pp. 44–53.

Mitrovic, J., Sejdinovic, D. and Teh, Y.-W. (2016) “DR-ABC: Approximate Bayesian computation with kernel-based distribution regression”, in ICML 2016: 33rd International Conference on Machine Learning. Journal of Machine Learning Research.

Sodjo, J. et al. (2016) “Joint Segmentation of Multiple Images with Shared Classes: A Bayesian Nonparametrics Approach”, in. Institute of Electrical and Electronics Engineers (IEEE), pp. 1–5.

Majeed, A. et al. (2016) “How would a decision to leave the European Union affect medical research and health in the United Kingdom?”, Journal of the Royal Society of Medicine, 109(6), pp. 216–218.

Kim, H. et al. (2016) “Collaborative Filtering with Side Information: a Gaussian Process Perspective.”

Lakshminarayanan, B., Roy, D. and Teh, Y. (2016) “Mondrian Forests for Large-Scale Regression when Uncertainty Matters”, in Proceedings of Machine Learning Research. 19th International Conference on Artificial Intelligence and Statistics, pp. 1478–1487.

Titsias, M., Holmes, C. and Yau, C. (2016) “Statistical Inference in Hidden Markov Models Using k-Segment Constraints”, Journal of the American Statistical Association, 111(513), pp. 200–215.

Bourhy, H. et al. (2016) “Revealing the Micro-scale Signature of Endemic Zoonotic Disease Transmission in an African Urban Setting”, PLOS Pathogens, 12(4), p. e1005525.

Teh, Y., Thiery, A. and Vollmer, S. (2016) “Consistency and fluctuations for stochastic gradient Langevin dynamics”, Journal of Machine Learning Research, 17(7), pp. 1–33.

Rebeschini, P. and Tatikonda, S. (2016) “Decay of Correlation in Network Flow Problems”, in. Institute of Electrical and Electronics Engineers (IEEE), pp. 169–174.