| Choosing between methods of combining -values NA Heard, P Rubin-Delanchy Biometrika 105 (1), 239-246, 2018 | 157 | 2018 |
| Bayesian cluster identification in single-molecule localization microscopy data P Rubin-Delanchy, GL Burn, J Griffié, DJ Williamson, NA Heard, AP Cope, ... Nature methods 12 (11), 1072-1076, 2015 | 134 | 2015 |
| A statistical interpretation of spectral embedding: the generalised random dot product graph P Rubin-Delanchy, J Cape, M Tang, CE Priebe Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | 123 | 2022 |
| On testing for impropriety of complex-valued Gaussian vectors AT Walden, P Rubin-Delanchy IEEE Transactions on Signal Processing 57 (3), 825-834, 2008 | 67 | 2008 |
| A Bayesian cluster analysis method for single-molecule localization microscopy data J Griffié, M Shannon, CL Bromley, L Boelen, GL Burn, DJ Williamson, ... Nature Protocols 11 (12), 2499-2514, 2016 | 51 | 2016 |
| 3D Bayesian cluster analysis of super-resolution data reveals LAT recruitment to the T cell synapse J Griffié, L Shlomovich, DJ Williamson, M Shannon, J Aaron, S Khuon, ... Scientific reports 7 (1), 4077, 2017 | 36 | 2017 |
| Network-wide anomaly detection via the Dirichlet process N Heard, P Rubin-Delanchy 2016 IEEE Conference on Intelligence and Security Informatics (ISI), 220-224, 2016 | 31 | 2016 |
| Kinematics of complex-valued time series P Rubin-Delanchy, AT Walden IEEE Transactions on Signal Processing 56 (9), 4189-4198, 2008 | 29 | 2008 |
| The multilayer random dot product graph A Jones, P Rubin-Delanchy arXiv preprint arXiv:2007.10455, 2020 | 25 | 2020 |
| Filtering automated polling traffic in computer network flow data N Heard, P Rubin-Delanchy, DJ Lawson 2014 IEEE Joint Intelligence and Security Informatics Conference, 268-271, 2014 | 25 | 2014 |
| Correction of multiple-blinking artifacts in photoactivated localization microscopy LG Jensen, TY Hoh, DJ Williamson, J Griffié, D Sage, P Rubin-Delanchy, ... Nature Methods 19 (5), 594-602, 2022 | 23 | 2022 |
| Manifold structure in graph embeddings P Rubin-Delanchy Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 2020 | 22 | 2020 |
| Dynamic Bayesian cluster analysis of live‐cell single molecule localization microscopy datasets J Griffié, GL Burn, DJ Williamson, R Peters, P Rubin‐Delanchy, DM Owen Small Methods 2 (9), 1800008, 2018 | 17 | 2018 |
| Simulation of improper complex-valued sequences P Rubin-Delanchy, AT Walden IEEE transactions on signal processing 55 (11), 5517-5521, 2007 | 17 | 2007 |
| Meta-analysis of mid-p-values: some new results based on the convex order P Rubin-Delanchy, NA Heard, DJ Lawson Journal of the American Statistical Association, 2018 | 15 | 2018 |
| Spectral embedding for dynamic networks with stability guarantees I Gallagher, A Jones, P Rubin-Delanchy Advances in Neural Information Processing Systems 34 (NeurIPS 2021), 2021 | 14 | 2021 |
| Spectral embedding of weighted graphs I Gallagher, A Jones, A Bertiger, C Priebe, P Rubin-Delanchy Journal of the American Statistical Association, 2023 | 12* | 2023 |
| Spectral clustering on spherical coordinates under the degree-corrected stochastic blockmodel FS Passino, NA Heard, P Rubin-Delanchy Technometrics 64 (3), 346-357, 2022 | 12 | 2022 |
| Spectral clustering under degree heterogeneity: a case for the random walk Laplacian A Modell, P Rubin-Delanchy arXiv preprint arXiv:2105.00987, 2021 | 12 | 2021 |
| Consistency of adjacency spectral embedding for the mixed membership stochastic blockmodel P Rubin-Delanchy, CE Priebe, M Tang arXiv preprint arXiv:1705.04518, 2017 | 12 | 2017 |
N A HeardImperial CollegeVerified email at imperial.ac.uk
