| Genetic effects on gene expression across human tissues GTEx Consortium Lead analysts: Aguet François 1 Brown Andrew A. 2 3 4 Castel ... Nature 550 (7675), 204-213, 2017 | 3126 | 2017 |
| Co-expression networks reveal the tissue-specific regulation of transcription and splicing A Saha, Y Kim, ADH Gewirtz, B Jo, C Gao, IC McDowell, BE Engelhardt, ... Genome research 27 (11), 1843-1858, 2017 | 160 | 2017 |
| Graph clustering with graph neural networks E Müller Journal of Machine Learning Research 24, 1-21, 2023 | 138 | 2023 |
| Community extraction in multilayer networks with heterogeneous community structure JD Wilson, J Palowitch, S Bhamidi, AB Nobel The Journal of Machine Learning Research 18 (1), 5458-5506, 2017 | 72 | 2017 |
| Identifying cis-mediators for trans-eQTLs across many human tissues using genomic mediation analysis F Yang, J Wang, BL Pierce, LS Chen, F Aguet, KG Ardlie, BB Cummings, ... Genome research 27 (11), 1859-1871, 2017 | 64 | 2017 |
| Graphworld: Fake graphs bring real insights for gnns J Palowitch, A Tsitsulin, B Mayer, B Perozzi Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 51 | 2022 |
| Significance-based community detection in weighted networks J Palowitch, S Bhamidi, AB Nobel The Journal of Machine Learning Research 18 (1), 6899-6946, 2017 | 42* | 2017 |
| Monet: Debiasing graph embeddings via the metadata-orthogonal training unit J Palowitch, B Perozzi arXiv preprint arXiv:1909.11793, 2019 | 28* | 2019 |
| Tf-gnn: Graph neural networks in tensorflow O Ferludin, A Eigenwillig, M Blais, D Zelle, J Pfeifer, A Sanchez-Gonzalez, ... arXiv preprint arXiv:2207.03522, 2022 | 15 | 2022 |
| Synthetic Graph Generation to Benchmark Graph Learning J Palowitch, A Tsitsulin, B Perozzi, BA Mayer NeurIPS 2022 Workshop: New Frontiers in Graph Learning, 2022 | 11* | 2022 |
| Estimation of cis‐eQTL effect sizes using a log of linear model J Palowitch, A Shabalin, YH Zhou, AB Nobel, FA Wright Biometrics 74 (2), 616-625, 2018 | 11 | 2018 |
| Computing the statistical significance of optimized communities in networks J Palowitch Scientific Reports 9 (1), 1-10, 2019 | 8 | 2019 |
| Zero-shot Transfer Learning within a Heterogeneous Graph via Knowledge Transfer Networks M Yoon, J Palowitch, D Zelle, Z Hu, R Salakhutdinov, B Perozzi Advances in Neural Information Processing Systems 35, 27347-27359, 2022 | 6 | 2022 |
| Recurrent graph neural networks for rumor detection in online forums D Huang, J Bartel, J Palowitch arXiv preprint arXiv:2108.03548, 2021 | 4 | 2021 |
| Graph Generative Model for Benchmarking Graph Neural Networks M Yoon, Y Wu, J Palowitch, B Perozzi, R Salakhutdinov | 3 | 2023 |
| Finding stable groups of cross-correlated features in multi-view data M Dewaskar, J Palowitch, M He, MI Love, A Nobel arXiv preprint arXiv:2009.05079, 2020 | 3 | 2020 |
| De-Biasing Graph Embeddings via Metadata-Orthogonal Training JJ Palowitch US Patent App. 17/000,732, 2021 | 2 | 2021 |
| Examining the Effects of Degree Distribution and Homophily in Graph Learning Models M Yasir, J Palowitch, A Tsitsulin, L Tran-Thanh, B Perozzi arXiv preprint arXiv:2307.08881, 2023 | 1 | 2023 |
| Scalable and Privacy-enhanced Graph Generative Model for Graph Neural Networks M Yoon, Y Wu, J Palowitch, B Perozzi, R Salakhutdinov | 1 | 2022 |
| Large-Scale Architecture Search in Graph Neural Networks via Synthetic Data BT Perozzi, A Tsitsulin, JJ Palowitch, B Mayer US Patent App. 17/940,568, 2023 | | 2023 |
Shankar BhamidiProfessor, University of North Carolina, Chapel HillVerified email at email.unc.edu
