Publications
Jacob, P. et al. (no date) “Better together? Statistical learning in models made of modules.”
Behme, A., Klüppelberg, C. and Reinert, G. (no date) “Hitting probabilities for compound Poisson processes in a bipartite network.”
Rao, D. et al. (no date) “Continual Unsupervised Representation Learning.”
Teh, Y., Elliott, L. and Blundell, C. (no date) “Bayesian Nonparametric Modelling of Genetic Variations using Fragmentation-Coagulation”, Journal of Machine Learning Research [Preprint].
Ernst, M., Reinert, G. and Swan, Y. (no date) “On infinite covariance expansions.”
Fathi, M. et al. (no date) “Relaxing the Gaussian assumption in Shrinkage and SURE in high dimension.”
Vollmer, S. et al. (no date) “Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness.”
Mathieu, E. et al. (no date) “Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders.”
Foster, A. et al. (no date) “Variational Bayesian Optimal Experimental Design.”