Publications

Clarkson, J. et al. (2022) “DAMNETS: a deep autoregressive model for generating Markovian network time series”, in Proceedings of the First Learning on Graphs Conference. Journal of Machine Learning Research, pp. 23:1 – 23:19.

Dupont, E. et al. (2022) “COIN++: neural compression across modalities”, Transactions on Machine Learning Research, 2022(11).

Cooper, J. et al. (2022) “Topological analysis of credit data: preliminary findings”, in Proceedings of the 23rd International Conference on Intelligent Data Engineering and Automated Learning (IDEAL). Springer, pp. 432–442.

Wu, F. and Rebeschini, P. (2022) “Nearly minimax-optimal rates for noisy sparse phase retrieval via early-stopped mirror descent”, Information and Inference: a Journal of the IMA, 12(2), pp. 633–713.

Bennett, S., Cucuringu, M. and Reinert, G. (2022) “Lead–lag detection and network clustering for multivariate time series with an application to the US equity market”, Machine Learning, 111(12), pp. 4497–4538.

Teh, Y. et al. (2022) “Authors’ Reply to the Discussion of ‘Efficient Bayesian Inference of Instantaneous Reproduction Numbers at Fine Spatial Scales, with an Application to Mapping and Nowcasting the Covid-19 Epidemic in British Local Authorities’ by Teh et al. in Session 2 of the Royal Statistical Society’s Special Topic Meeting on COVID-19 Transmission: 11 June 2021”, Journal of the Royal Statistical Society Series A (Statistics in Society), 185(Supplement_1), pp. s107 - s109.

Anastasiou, A. et al. (2022) “Stein’s method meets computational statistics: a review of some recent developments”, Statistical Science, 38(1), pp. 120–139.

Fathi, M. et al. (2022) “Relaxing the Gaussian assumption in shrinkage and SURE in high dimension”, Annals of Statistics, 50(5), pp. 2737–2766.

Weckbecker, M., Xu, W. and Reinert, G. (2022) “On RKHS choices for assessing graph generators via kernel Stein statistics.”

Limnios, S. et al. (2022) “Random walk based conditional generative model for temporal networks with attributes ”, in Advances in Neural Information Processing Systems 36 (NeurIPS 2022). Neural Information Processing Systems Foundation.