Publications by Probability

He, Y. et al. (2022) “GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks.”

Foutel-Rodier, F. and Schertzer, E. (2022) “Convergence of genealogies through spinal decomposition with an application to population genetics”, arXiv.

Bennett, S., Cucuringu, M. and Reinert, G. (2022) “Lead-lag detection and network clustering for multivariate time series with an application to the US equity market.”

Ernst, M., Reinert, G. and Swan, Y. (2022) “On Papathanasiou’s covariance expansions”, Latin American Journal of Probability and Mathematical Statistics, 19(2), pp. 1827 – 1827.

He, Y., Reinert, G. and Cucuringu, M. (2022) “DIGRAC: Digraph Clustering Based on Flow Imbalance”, in Proceedings of Machine Learning Research.

Xu, W. and Reinert, G. (2022) “AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph Generators”, in Advances in Neural Information Processing Systems.

He, Y. et al. (2022) “MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian”, in Proceedings of Machine Learning Research.

Xu, W. and Reinert, G. (2022) “A Kernelised Stein Statistic for Assessing Implicit Generative Models”, in Advances in Neural Information Processing Systems.

Temčinas, T., Nanda, V. and Reinert, G. (2021) “Multivariate Central Limit Theorems for Random Clique Complexes”, arXiv.

Berestycki, J. et al. (2021) “The extremal point process of branching Brownian motion in $\mathbb{R}^d$”, arXiv.