| Coauthorship and citation networks for statisticians (with discussions) P Ji, J Jin The Annals of Applied Statistics 10 (4), 1779-1812, 2016 | 176* | 2016 |
| Predictors of secondary traumatic stress among social workers: Supervision, income, and caseload size A Quinn, P Ji, L Nackerud Journal of Social Work 19 (4), 504-528, 2019 | 132 | 2019 |
| UPS delivers optimal phase diagram in high-dimensional variable selection P Ji, J Jin Annals of Statistics 40 (1), 73-103, 2012 | 111 | 2012 |
| CensNet: Convolution with Edge-Node Switching in Graph Neural Networks. X Jiang, P Ji, S Li International Joint Conferences on Artificial Intelligence (IJCAI), 2656-2662, 2019 | 70 | 2019 |
| Discussion on "Statistical modelling of citation exchange between statistics journals" P Ji, J Jin, ZT Ke Journal of the Royal Statistical Society: Series A 179 (1), 52-53, 2016 | 69* | 2016 |
| Co-embedding of nodes and edges with graph neural networks X Jiang, R Zhu, S Li, P Ji IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020 | 61 | 2020 |
| Co-citation and Co-authorship Networks of Statisticians (with discussions) P Ji, J Jin, ZT Ke, W Li Journal of Business & Economic Statistics 40 (2), 469-485, 2022 | 43 | 2022 |
| Spectral algorithms for community detection in directed networks Z Wang, Y Liang, P Ji Journal of Machine Learning Research, 2020 | 22 | 2020 |
| Rate optimal multiple testing procedure in high-dimensional regression P Ji, Z Zhao arXiv preprint arXiv:1404.2961, 2014 | 21 | 2014 |
| Using the statistical program R instead of SPSS to analyze data H Tang, P Ji Tools of Chemistry Education Research, 135-151, 2014 | 13 | 2014 |
| An R package for SNP marker-based parent-offspring tests H Abdel-Haleem, P Ji, HR Boerma, Z Li Plant methods 9, 1-5, 2013 | 10 | 2013 |
| The species coalescent indicates possible bat and pangolin origins of the COVID-19 pandemic J Yang, M Skaro, J Chen, D Zhan, L Lyu, S Gay, A Kandeil, MA Ali, ... Scientific Reports 13 (1), 5571, 2023 | 5 | 2023 |
| Sharp minimax adaptation over Sobolev ellipsoids in nonparametric testing P Ji, M Nussbaum | 2 | 2017 |
| Open-Set Graph Domain Adaptation via Separate Domain Alignment Y Wang, R Zhu, P Ji, S Li Proceedings of the AAAI Conference on Artificial Intelligence 38 (8), 9142-9150, 2024 | 1 | 2024 |
| Recent advances in text analysis ZT Ke, P Ji, J Jin, W Li Annual Review of Statistics and Its Application 11, 2023 | 1 | 2023 |
| Rejoinder:“Co-citation and Co-authorship Networks of Statisticians” P Ji, J Jin, ZT Ke, W Li Journal of Business & Economic Statistics 40 (2), 499-504, 2022 | 1 | 2022 |
| Sharp adaptive nonparametric testing for Sobolev ellipsoids P Ji, M Nussbaum arXiv preprint arXiv:1210.8162, 2012 | 1 | 2012 |
| Selected Topics In Nonparametric Testing And Variable Selection For High Dimensional Data P Ji | 1 | 2012 |
| Supplementary material for “ups delivers optimal phase diagram in high dimensional variable selection” P Ji, J Jin | 1 | 2011 |
| Bridging the Fairness Divide: Achieving Group and Individual Fairness in Graph Neural Networks D Zhan, D Guo, P Ji, S Li | | 2023 |
Jiashun JinProfessor of Statistics, Carnegie Mellon UniversityVerified email at stat.cmu.edu
