Poisson Process Approximation for Repeats in One Sequence and Its Application to Sequencing by Hybridization. - Richard Arratia; Gesine Reinert (CPM, 1996)

Poisson Process Approximation for Sequence Repeats and Sequencing by Hybridization. - Richard Arratia; Daniela Martin; Gesine Reinert; Michael S. Waterman (J. Comput. Biol., 1996)

Couplings for normal approximations with Stein's method. - Gesine Reinert (Microsurveys in Discrete Probability, 1997)

Compound Poisson and Poisson Process Approximations for Occurrences of Multiple Words in Markov Chains. - Gesine Reinert; Sophie Schbath (J. Comput. Biol., 1998)

Probabilistic and Statistical Properties of Words: An Overview. - Gesine Reinert; Sophie Schbath; Michael S. Waterman (J. Comput. Biol., 2000)

Small worlds. - Andrew D. Barbour; Gesine Reinert (Random Struct. Algorithms, 2001)

Correction: Small worlds. - Andrew D. Barbour; Gesine Reinert (Random Struct. Algorithms, 2004)

A statistical approach using network structure in the prediction of protein characteristics. - Pao-Yang Chen; Charlotte M. Deane; Gesine Reinert (Bioinform., 2007)

On the Length of the Longest Exact Position Match in a Random Sequence. - Gesine Reinert; Michael S. Waterman (IEEE ACM Trans. Comput. Biol. Bioinform., 2007)

Predicting and Validating Protein Interactions Using Network Structure. - Pao-Yang Chen; Charlotte M. Deane; Gesine Reinert (PLoS Comput. Biol., 2008)

Alignment-Free Sequence Comparison (I): Statistics and Power. - Gesine Reinert; David Chew; Fengzhu Sun; Michael S. Waterman (J. Comput. Biol., 2009)

How threshold behaviour affects the use of subgraphs for network comparison. - Tiago Rito; Zi Wang; Charlotte M. Deane; Gesine Reinert (Bioinform., 2010)

Deciphering chemotaxis pathways using cross species comparisons. - Rebecca Hamer; Pao-Yang Chen; Judith P. Armitage; Gesine Reinert; Charlotte M. Deane (BMC Syst. Biol., 2010)

Alignment-Free Sequence Comparison (II): Theoretical Power of Comparison Statistics. - Lin Wan; Gesine Reinert; Fengzhu Sun; Michael S. Waterman (J. Comput. Biol., 2010)

The Power of Detecting Enriched Patterns: An HMM Approach. - Zhiyuan Zhai; Shih-Yen Ku; Yihui Luan; Gesine Reinert; Michael S. Waterman; Fengzhu Sun (J. Comput. Biol., 2010)

The shortest distance in random multi-type intersection graphs. - Andrew D. Barbour; Gesine Reinert (Random Struct. Algorithms, 2011)

Asymptotic behaviour of gossip processes and small world networks - Andrew D. Barbour; Gesine Reinert (CoRR, 2012)

The Importance of Age and High Degree, in Protein-Protein Interaction Networks. - Tiago Rito; Charlotte M. Deane; Gesine Reinert (J. Comput. Biol., 2012)

Normal and Compound Poisson Approximations for Pattern Occurrences in NGS Reads. - Zhiyuan Zhai; Gesine Reinert; Kai Song; Michael S. Waterman; Yihui Luan; Fengzhu Sun (J. Comput. Biol., 2012)

Multiple alignment-free sequence comparison. - Jie Ren 006; Kai Song; Fengzhu Sun; Minghua Deng; Gesine Reinert (Bioinform., 2013)

Stein's Method for the Beta Distribution and the Pólya-Eggenberger Urn. - Larry Goldstein; Gesine Reinert (J. Appl. Probab., 2013)

New developments of alignment-free sequence comparison: measures, statistics and next-generation sequencing. - Kai Song; Jie Ren 006; Gesine Reinert; Minghua Deng; Michael S. Waterman; Fengzhu Sun (Briefings Bioinform., 2014)

Alignment-free protein interaction network comparison. - Waqar Ali; Tiago Rito; Gesine Reinert; Fengzhu Sun; Charlotte M. Deane (Bioinform., 2014)

Inference of Markovian properties of molecular sequences from NGS data and applications to comparative genomics. - Jie Ren 006; Kai Song; Minghua Deng; Gesine Reinert; Charles H. Cannon; Fengzhu Sun (Bioinform., 2016)

Estimating the number of communities in a network. - M. E. J. Newman; Gesine Reinert (CoRR, 2016)

Risk in a Large Claims Insurance Market with Bipartite Graph Structure. - Oliver Kley; Claudia Klüppelberg; Gesine Reinert (Oper. Res., 2016)

Efficient method for estimating the number of communities in a network. - Maria A. Riolo; George T. Cantwell; Gesine Reinert; Mark E. J. Newman (CoRR, 2017)

Triad-Based Comparison and Signatures of Directed Networks. - Xiaochuan Xu; Gesine Reinert (COMPLEX NETWORKS (1), 2018)

A nonparametric significance test for sampled networks. - Andrew Elliott; Elizabeth Leicht; Alan Whitmore; Gesine Reinert; Felix Reed-Tsochas (Bioinform., 2018)

CommWalker: correctly evaluating modules in molecular networks in light of annotation bias. - Malte Lücken; M. J. T. Page; A. J. Crosby; S. Mason; Gesine Reinert; Charlotte M. Deane (Bioinform., 2018)

Identifying networks with common organizational principles. - Anatol E. Wegner; Luis Ospina-Forero; Robert E. Gaunt; Charlotte M. Deane; Gesine Reinert (J. Complex Networks, 2018)

Measuring rank robustness in scored protein interaction networks. - Lyuba V. Bozhilova; Alan Whitmore; Jonny Wray; Gesine Reinert; Charlotte M. Deane (BMC Bioinform., 2019)

Assessment of model fit via network comparison methods based on subgraph counts. - Luis Ospina-Forero; Charlotte M. Deane; Gesine Reinert (J. Complex Networks, 2019)

Anomaly Detection in Networks with Application to Financial Transaction Networks. - Andrew Elliott; Mihai Cucuringu; Milton Martinez Luaces; Paul Reidy; Gesine Reinert (CoRR, 2019)

Core-Periphery Structure in Directed Networks. - Andrew Elliott; Angus Chiu; Marya Bazzi; Gesine Reinert; Mihai Cucuringu (CoRR, 2019)

A bound on the rate of convergence in the central limit theorem for renewal processes under second moment conditions. - Gesine Reinert; Ce Yang (J. Appl. Probab., 2020)

A Stein Goodness-of-test for Exponential Random Graph Models. - Wenkai Xu; Gesine Reinert (AISTATS, 2021)

COGENT: evaluating the consistency of gene co-expression networks. - Lyuba V. Bozhilova; Javier Pardo-Diaz; Gesine Reinert; Charlotte M. Deane (Bioinform., 2021)

Robust gene coexpression networks using signed distance correlation. - Javier Pardo-Diaz; Lyuba V. Bozhilova; Mariano Beguerisse-Díaz; Philip S. Poole; Charlotte M. Deane; Gesine Reinert (Bioinform., 2021)

Estimating the correlation in network disturbance models. - Andrew D. Barbour; Gesine Reinert (J. Complex Networks, 2021)

Hypergraphs for predicting essential genes using multiprotein complex data. - Florian Klimm; Charlotte M. Deane; Gesine Reinert (J. Complex Networks, 2021)

DIGRAC: Digraph Clustering with Flow Imbalance. - Yixuan He; Gesine Reinert; Mihai Cucuringu (CoRR, 2021)

GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks. - Yixuan He; Quan Gan; David Wipf; Gesine D. Reinert; Junchi Yan; Mihai Cucuringu (ICML, 2022)

Topological Analysis of Credit Data: Preliminary Findings. - James Cooper; Peter Mitic; Gesine Reinert; Tadas Temcinas (IDEAL, 2022)

DAMNETS: A Deep Autoregressive Model for Generating Markovian Network Time Series. - Jase Clarkson; Mihai Cucuringu; Andrew Elliott; Gesine Reinert (LoG, 2022)

MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian. - Yixuan He; Michael Perlmutter; Gesine Reinert; Mihai Cucuringu (LoG, 2022)

DIGRAC: Digraph Clustering Based on Flow Imbalance. - Yixuan He; Gesine Reinert; Mihai Cucuringu (LoG, 2022)

A Kernelised Stein Statistic for Assessing Implicit Generative Models. - Wenkai Xu; Gesine D. Reinert (NeurIPS, 2022)

AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph Generators. - Wenkai Xu; Gesine D. Reinert (NeurIPS, 2022)

SSSNET: Semi-Supervised Signed Network Clustering. - Yixuan He; Gesine Reinert; Songchao Wang; Mihai Cucuringu (SDM, 2022)

Ranking of communities in multiplex spatiotemporal models of brain dynamics. - James B. Wilsenach; Catherine E. Warnaby; Charlotte M. Deane; Gesine Reinert (Appl. Netw. Sci., 2022)

PyTorch Geometric Signed Directed: A Survey and Software on Graph Neural Networks for Signed and Directed Graphs. - Yixuan He; Xitong Zhang; Junjie Huang; Mihai Cucuringu; Gesine Reinert (CoRR, 2022)

On RKHS Choices for Assessing Graph Generators via Kernel Stein Statistics. - Moritz Weckbecker; Wenkai Xu; Gesine Reinert (CoRR, 2022)

Extracting Information from Gene Coexpression Networks of Rhizobium leguminosarum. - Javier Pardo-Diaz; Mariano Beguerisse-Díaz; Philip S. Poole; Charlotte M. Deane; Gesine Reinert (J. Comput. Biol., 2022)

Lead-lag detection and network clustering for multivariate time series with an application to the US equity market. - Stefanos Bennett; Mihai Cucuringu; Gesine Reinert (Mach. Learn., 2022)

Generating weighted and thresholded gene coexpression networks using signed distance correlation. - Javier Pardo-Diaz; Philip S. Poole; Mariano Beguerisse-Díaz; Charlotte M. Deane; Gesine Reinert (Netw. Sci., 2022)

L2G2G: A Scalable Local-to-Global Network Embedding with Graph Autoencoders. - Ruikang Ouyang; Andrew Elliott; Stratis Limnios; Mihai Cucuringu; Gesine Reinert (COMPLEX NETWORKS (1), 2023)

PyTorch Geometric Signed Directed: A Software Package on Graph Neural Networks for Signed and Directed Graphs. - Yixuan He; Xitong Zhang; Junjie Huang; Benedek Rozemberczki; Mihai Cucuringu; Gesine Reinert (LoG, 2023)

The GNAR-edge model: a network autoregressive model for networks with time-varying edge weights. - Anastasia Mantziou; Mihai Cucuringu; Victor Meirinhos; Gesine Reinert (J. Complex Networks, 2023)

Split Conformal Prediction under Data Contamination. - Jason Clarkson; Wenkai Xu; Mihai Cucuringu; Gesine Reinert (COPA, 2024)

SaGess: A Sampling Graph Denoising Diffusion Model for Scalable Graph Generation. - Stratis Limnios; Praveen Selvaraj; Mihai Cucuringu; Carsten Maple; Gesine Reinert; Andrew Elliott (ECAI, 2024)

Robust Angular Synchronization via Directed Graph Neural Networks. - Yixuan He; Gesine Reinert; David Wipf; Mihai Cucuringu (ICLR, 2024)

Generalization Error of Graph Neural Networks in the Mean-field Regime. - Gholamali Aminian; Yixuan He; Gesine Reinert; Lukasz Szpruch; Samuel N. Cohen (ICML, 2024)

SteinGen: Generating Fidelitous and Diverse Graph Samples. - Gesine Reinert; Wenkai Xu (CoRR, 2024)

Generalization Error of the Tilted Empirical Risk. - Gholamali Aminian; Amir R. Asadi; Tian Li; Ahmad Beirami; Gesine Reinert; Samuel N. Cohen (CoRR, 2024)

Multivariate central limit theorems for random clique complexes. - Tadas Temcinas; Vidit Nanda; Gesine Reinert (J. Appl. Comput. Topol., 2024)

Network-based time series modeling for COVID-19 incidence in the Republic of Ireland. - Stephanie Armbruster; Gesine Reinert (Appl. Netw. Sci., 2024)

Individualised Counterfactual Examples Using Conformal Prediction Intervals. - James M. Adams; Gesine Reinert; Lukasz Szpruch; Carsten Maple; Andrew Elliott (COPA, 2025)

Learning to Fuse Temporal Proximity Networks: A Case Study in Chimpanzee Social Interactions. - Yixuan He; Aaron Sandel; David Wipf; Mihai Cucuringu; John Mitani; Gesine Reinert (CoRR, 2025)

Private Synthetic Graph Generation and Fused Gromov-Wasserstein Distance. - Leoni Carla Wirth; Gholamali Aminian; Gesine Reinert (CoRR, 2025)

A Kernelised Stein Discrepancy for Assessing the Fit of Inhomogeneous Random Graph Models. - Anum Fatima; Gesine Reinert (CoRR, 2025)

A Bayesian mixture model for Poisson network autoregression. - Elly Hung; Anastasia Mantziou; Gesine Reinert (Soc. Netw. Anal. Min., 2025)