Gesine Reinert

Gesine Reinert

University of Oxford

H-index: 34

Europe-United Kingdom

About Gesine Reinert

Gesine Reinert, With an exceptional h-index of 34 and a recent h-index of 24 (since 2020), a distinguished researcher at University of Oxford, specializes in the field of Applied Probability, Statistics, Networks, Computational Biology.

His recent articles reflect a diverse array of research interests and contributions to the field:

Network-based time series modeling for COVID-19 incidence in the Republic of Ireland

SteinGen: Generating Fidelitous and Diverse Graph Samples

Generalization Error of Graph Neural Networks in the Mean-field Regime

Pytorch geometric signed directed: a software package on graph neural networks for signed and directed graphs

Multivariate central limit theorems for random clique complexes

Sagess: Sampling graph denoising diffusion model for scalable graph generation

Co-trading networks for modeling dynamic interdependency structures and estimating high-dimensional covariances in US equity markets

Robust Angular Synchronization via Directed Graph Neural Networks

Gesine Reinert Information

University

Position

Professor of Statistics

Citations(all)

4550

Citations(since 2020)

2031

Cited By

3437

hIndex(all)

34

hIndex(since 2020)

24

i10Index(all)

79

i10Index(since 2020)

54

Email

University Profile Page

University of Oxford

Google Scholar

View Google Scholar Profile

Gesine Reinert Skills & Research Interests

Applied Probability

Statistics

Networks

Computational Biology

Top articles of Gesine Reinert

Title

Journal

Author(s)

Publication Date

Network-based time series modeling for COVID-19 incidence in the Republic of Ireland

Stephanie Armbruster

Gesine Reinert

2024/4/5

SteinGen: Generating Fidelitous and Diverse Graph Samples

arXiv preprint arXiv:2403.18578

Gesine Reinert

Wenkai Xu

2024/3/27

Generalization Error of Graph Neural Networks in the Mean-field Regime

arXiv preprint arXiv:2402.07025

Gholamali Aminian

Yixuan He

Gesine Reinert

Łukasz Szpruch

Samuel N Cohen

2024/2/10

Pytorch geometric signed directed: a software package on graph neural networks for signed and directed graphs

arXiv preprint arXiv:2202.10793

Yixuan He

Xitong Zhang

Junjie Huang

Benedek Rozemberczki

Mihai Cucuringu

...

2022/2/22

Multivariate central limit theorems for random clique complexes

Journal of Applied and Computational Topology

Tadas Temčinas

Vidit Nanda

Gesine Reinert

2023/10/21

Sagess: Sampling graph denoising diffusion model for scalable graph generation

arXiv preprint arXiv:2306.16827

Stratis Limnios

Praveen Selvaraj

Mihai Cucuringu

Carsten Maple

Gesine Reinert

...

2023/6/29

Co-trading networks for modeling dynamic interdependency structures and estimating high-dimensional covariances in US equity markets

arXiv preprint arXiv:2302.09382

Yutong Lu

Gesine Reinert

Mihai Cucuringu

2023/2/18

Robust Angular Synchronization via Directed Graph Neural Networks

arXiv preprint arXiv:2310.05842

Yixuan He

Gesine Reinert

David Wipf

Mihai Cucuringu

2023/10/9

The Costs and Benefits of Uniformly Valid Causal Inference with High-Dimensional Nuisance Parameters.............. Niloofar Moosavi, Jenny Häggström and Xavier de Luna 1 …

Statistical Science [ISSN 0883-4237 (print); ISSN 2168-8745 (online)]

Elvezio Ronchetti

Andrej Ilievski

Alessandra Giovagnoli

Isabella Verdinelli

Rajen D Shah

...

2023/2

Goodness-of-fit via Count Statistics in Dense Random Simplicial Complexes

arXiv preprint arXiv:2309.14017

Tadas Temčinas

Vidit Nanda

Gesine Reinert

2023/9/25

Bounds for the chi-square approximation of Friedman’s statistic by Stein’s method

Bernoulli

Robert E Gaunt

Gesine Reinert

2023/8

The GNAR-edge model: a network autoregressive model for networks with time-varying edge weights

Journal of Complex Networks

Anastasia Mantziou

Mihai Cucuringu

Victor Meirinhos

Gesine Reinert

2023/12/1

Stein’s density method for multivariate continuous distributions

Electronic Journal of Probability

Guillaume Mijoule

Martin Raič

Gesine Reinert

Yvik Swan

2023

L2G2G: A Scalable Local-to-Global Network Embedding with Graph Autoencoders

Ruikang Ouyang

Andrew Elliott

Stratis Limnios

Mihai Cucuringu

Gesine Reinert

2023/11/28

COVID-19 incidence in the Republic of Ireland: A case study for network-based time series models

arXiv preprint arXiv:2307.06199

Stephanie Armbruster

Gesine Reinert

2023/7/12

Trade co-occurrence, trade flow decomposition, and conditional order imbalance in equity markets

arXiv preprint arXiv:2209.10334

Yutong Lu

Gesine Reinert

Mihai Cucuringu

2022/9/21

Lead–lag detection and network clustering for multivariate time series with an application to the US equity market

Machine Learning

Stefanos Bennett

Mihai Cucuringu

Gesine Reinert

2022/12

DAMNETS: A deep autoregressive model for generating Markovian network time series

Jase Clarkson

Mihai Cucuringu

Andrew Elliott

Gesine Reinert

2022/12/21

Ranking of communities in multiplex spatiotemporal models of brain dynamics

Applied Network Science

James B Wilsenach

Catherine E Warnaby

Charlotte M Deane

Gesine D Reinert

2022/3/14

Normal approximation for the posterior in exponential families

arXiv preprint arXiv:2209.08806

Adrian Fischer

Robert E Gaunt

Gesine Reinert

Yvik Swan

2022/9/19

See List of Professors in Gesine Reinert University(University of Oxford)