Oxford university logo and department of statistics logo

To Department of Statistics Site

 Menu

Publications

Ghalebikesabi, S. et al. (2021) “Deep Generative Missingness Pattern-Set Mixture Models”, in Proceedings of Machine Learning Research, pp. 3727–3735.
Hayou, S. et al. (2021) “ROBUST PRUNING AT INITIALIZATION”, in ICLR 2021 - 9th International Conference on Learning Representations.
Ghalebikesabi, S. et al. (2021) “On Locality of Local Explanation Models”, in Advances in Neural Information Processing Systems, pp. 18395–18407.
Pardo-Diaz, J. et al. (2021) “Generating weighted and thresholded gene coexpression networks using signed distance correlation”, bioRxiv.
Wilde, H. et al. (2021) “Foundations of Bayesian Learning from Synthetic Data”, in Proceedings of Machine Learning Research, pp. 541–549.
Naik, C., Caron, F. and Rousseau, J. (2021) “Sparse networks with core-periphery structure”, Electronic Journal of Statistics, 15(1), pp. 1814–1868.
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.