Publications

Clivio, O., Feller, A. and Holmes, C. (2024) “Towards Representation Learning for Weighting Problems in Design-Based Causal Inference”, in Proceedings of Machine Learning Research, pp. 856–880.

Johnson, E., Pike-Burke, C. and Rebeschini, P. (2023) “Optimal convergence rate for exact policy mirror descent in discounted Markov decision processes”, in Advances in Neural Information Processing Systems. NeurIPS, pp. 76496–76524.

Kanade, V., Rebeschini, P. and Vaskevicius, T. (2023) “The statistical complexity of early-stopped mirror descent”, Information and Inference: A Journal of the IMA, 12(4), pp. 3010–3041.

Mantziou, A. et al. (2023) “The GNAR-edge model: a network autoregressive model for networks with time-varying edge weights”, Journal of Complex Networks, 11(6).

Jiang, X. et al. (2023) “Age-dependent topic modeling of comorbidities in UK Biobank identifies disease subtypes with differential genetic risk”, Nature Genetics, 55(11), pp. 1854–1865.

Torabi, F. et al. (2023) “Wastewater-based surveillance models for COVID-19: A focused review on spatio-temporal models”, Heliyon, 9(11), p. e21734.

Huh, J. and Rebeschini, P. (2023) “Generalization bounds for label noise stochastic gradient descent”, arXiv.

Temčinas, T., Nanda, V. and Reinert, G. (2023) “Multivariate central limit theorems for random clique complexes”, Journal of Applied and Computational Topology, 8(6), pp. 1837–1880.

Reinert, G., Nanda, V. and Temcinas, T. (2023) “Multivariate central limit theorems for random clique complexes”, Journal of Applied and Computational Topology [Preprint].

He, Y. et al. (2023) “Robust Angular Synchronization via Directed Graph Neural Networks”, arXiv.