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Publications

Falck, F. et al. (2021) “Multi-Facet Clustering Variational Autoencoders”, in Advances in Neural Information Processing Systems, pp. 8676–8690.
Falck, F. et al. (2021) “Multi-Facet Clustering Variational Autoencoders”, in Advances in Neural Information Processing Systems, pp. 8676–8690.
Di Benedetto, G., Caron, F. and Teh, Y. (2020) “Non-exchangeable random partition models for microclustering”. University of Oxford.
Di Benedetto, G., Caron, F. and Teh, Y. (2020) “Non-exchangeable random partition models for microclustering”. University of Oxford.
Willetts, M., Roberts, S. and Holmes, C. (2020) “Semi-Unsupervised Learning: Clustering and Classifying using Ultra-Sparse Labels”, in. Institute of Electrical and Electronics Engineers (IEEE), pp. 5286–5295.
Wu, F. and Rebeschini, P. (2020) “A continuous-time mirror descent approach to sparse phase retrieval”, in Advances in Neural Information Processing Systems 33 (NeurIPS 2020). Neural Information Processing Systems Foundation, Inc., pp. 1–12.
Vaškevičius, T., Kanade, V. and Rebeschini, P. (2020) “The statistical complexity of early-stopped mirror descent”, in. Neural Information Processing Systems Foundation, Inc., pp. 1–12.
Watson, J. and Holmes, C. (2020) “Machine learning analysis plans for randomised controlled trials: detecting treatment effect heterogeneity with strict control of type I error”, Trials, 21(1), p. 156.
Watson, J. and Holmes, C. (2020) “Correction to: Graphing and reporting heterogeneous treatment effects through reference classes”, Trials, 21(1), p. 865.
Watson, J. and Holmes, C. (2020) “Graphing and reporting heterogeneous treatment effects through reference classes”, Trials, 21(1), p. 386.