Publications

Baudry, D. et al. (2025) “Does stochastic gradient really succeed for bandits?”, in.

Kilian, V., Cortinovis, S. and Caron, F. (2025) “Anytime-valid, Bayes-assisted, prediction-powered inference”, in. Neural Information Processing Systems Foundation.

Alfano, C. et al. (2025) “Meta-Learning Objectives for Preference Optimization”, in.

Ganjgahi, H. et al. (2025) “AI-driven reclassification of multiple sclerosis progression”, Nature Medicine, 31(10), pp. 3414–3424.

Temcinas, T., Nanda, V. and Reinert, G. (2025) “Goodness-of-fit via count statistics in dense random simplicial complexes”, Foundations of Data Science [Preprint].

Farghly, T. et al. (2025) “Implicit Regularisation in Diffusion Models: An Algorithm-Dependent Generalisation Analysis”, arXiv.

Johnson, E. et al. (2025) “On the necessity of adaptive regularisation:Optimal anytime online learning on $\boldsymbol{\ell_p}$-balls.”

Fatima, A. and Reinert, G. (2025) “Stein’s method for distributions modelling competing and complementary risk problems”, Advances in Applied Probability [Preprint].

Reinert, G., Hung, E. and Mantziou, A. (2025) “A Bayesian mixture model for Poisson network autoregression”, Social Network Analysis and Mining [Preprint].

Liu, X. et al. (2025) “Non-stationary Bandit Convex Optimization: A Comprehensive Study.”