Publications (Computational Statistics and Machine Learning) | Department of Statistics

Publications

Todeschini, A., Miscouridou, X. and Caron, F. (2016) “Exchangeable Random Measures for Sparse and Modular Graphs with Overlapping Communities”, arXiv.

Teh, Y. (2016) “Bayesian Nonparametric Modeling and the Ubiquitous Ewens Sampling Formula”, Statistical Science, 31(1), pp. 34–36.

Caron, F. (2016) “Book Review: Nonlinear Time Series: Theory, methods, and applications with R examples, by Randal Douc, Eric Moulines, David S. Stoffer”, Statistics and Computing, 26(1-2), pp. 571–572.

Coulson, M., Gaunt, R. and Reinert, G. (2016) “Poisson approximation of subgraph counts in stochastic block models and a graphon model”, ESAIM: Probability and Statistics [Preprint].

McGree, J. et al. (2016) “Big data and design of experiments”, in Computational and Statistical Methods for Analysing Big Data with Applications, pp. 111–129.

Patel, H. and Morris, G. (2016) “Novelty score: Prioritising compounds that potentially form novel protein-ligand interactions and novel scaffolds using an interaction centric approach”, ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY.

Vollmer, S., Zygalakis, K. and Teh, Y. (2016) “Exploration of the (non-)asymptotic bias and variance of stochastic gradient Langevin dynamics”, Journal of Machine Learning Research, 17(9), pp. 1–33.

Daly, A. et al. (2015) “Hodgkin–Huxley revisited: reparametrization and identifiability analysis of the classic action potential model with approximate Bayesian methods”, Royal Society Open Science, 2(12), p. Article number: 150499 - Article number: 150499-.

Stiphout, R. et al. (2015) “Abstract B1-56: Distinct roles of copy number and loss-of-heterozygosity in predicting prognosis for breast cancer patients”, in Cancer Research. American Association for Cancer Research (AACR), pp. b1–56.

James, L., Orbanz, P. and Teh, Y. (2015) “Scaled subordinators and generalizations of the Indian buffet process.”