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University of Oxford, Department of Statistics logo
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Publications

Xu, J. et al. (2021) “Group Equivariant Subsampling”, in Advances in Neural Information Processing Systems, pp. 5934–5946.
Tolpin, D. et al. (2021) “Probabilistic Programs with Stochastic Conditioning”, in Proceedings of Machine Learning Research, pp. 10312–10323.
Xu, J. et al. (2021) “Group Equivariant Subsampling”, in Advances in Neural Information Processing Systems, pp. 5934–5946.
Ivanova, D. et al. (2021) “Implicit Deep Adaptive Design: Policy-Based Experimental Design without Likelihoods”, in Advances in Neural Information Processing Systems, pp. 25785–25798.
Farquhar, S., Gal, Y. and Rainforth, T. (2021) “ON STATISTICAL BIAS IN ACTIVE LEARNING: HOW AND WHEN TO FIX IT”, in Iclr 2021 9th International Conference on Learning Representations.
Foster, A., Pukdee, R. and Rainforth, T. (2021) “IMPROVING TRANSFORMATION INVARIANCE IN CONTRASTIVE REPRESENTATION LEARNING”, in Iclr 2021 9th International Conference on Learning Representations.
Klimm, F., Deane, C. and Reinert, G. (2021) “Hypergraphs for predicting essential genes using multiprotein complex data”, J. Complex Networks, 9.
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.