Publications

Newman, M. and Reinert, G. (2016) “Estimating the number of communities in a network”, Physical Review Letters, 117(7).

Reinert, G., Kley, O. and Klueppelberg, C. (2016) “Risk in a large claims insurance market with bipartite graph structure”, Operations Research, 64(5), pp. 1159–1176.

Gray-Davies, T., Holmes, C. and Caron, F. (2016) “Scalable Bayesian nonparametric regression via a Plackett-Luce model for conditional ranks”, Electronic Journal of Statistics, 10(2), pp. 1807–1828.

Reinert, G. et al. (2016) “Comparison of large networks with sub-sampling strategies”, Scientific Reports [Preprint].

Naik, C. et al. (2016) “Bayesian Nonparametrics for Sparse Dynamic Networks”, arXiv.

Balog, M. et al. (2016) “The Mondrian kernel”, in UAI’16: Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence. AUAI Press, pp. 32–41.

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.

Doucet, A. et al. (2016) “Interacting particle Markov chain Monte Carlo”, in ICML 2016: 33rd International Conference on Machine Learning. Journal of Machine Learning Research.

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.