| Inductive representation learning on large graphs W Hamilton, Z Ying, J Leskovec Advances in neural information processing systems 30, 2017 | 14530 | 2017 |
| node2vec: Scalable feature learning for networks A Grover, J Leskovec Proceedings of the 22nd ACM SIGKDD international conference on Knowledge …, 2016 | 11646 | 2016 |
| How powerful are graph neural networks? K Xu, W Hu, J Leskovec, S Jegelka arXiv preprint arXiv:1810.00826, 2018 | 7198 | 2018 |
| SNAP Datasets: Stanford large network dataset collection J Leskovec, A Krevl | 4328 | 2014 |
| Friendship and mobility: user movement in location-based social networks E Cho, SA Myers, J Leskovec Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 3608 | 2011 |
| Graph convolutional neural networks for web-scale recommender systems R Ying, R He, K Chen, P Eksombatchai, WL Hamilton, J Leskovec Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018 | 3474 | 2018 |
| Graph evolution: Densification and shrinking diameters J Leskovec, J Kleinberg, C Faloutsos ACM transactions on Knowledge Discovery from Data (TKDD) 1 (1), 2-es, 2007 | 3253 | 2007 |
| Graphs over time: densification laws, shrinking diameters and possible explanations J Leskovec, J Kleinberg, C Faloutsos Proceedings of the eleventh ACM SIGKDD international conference on Knowledge …, 2005 | 3237 | 2005 |
| The dynamics of viral marketing J Leskovec, LA Adamic, BA Huberman ACM Transactions on the Web (TWEB) 1 (1), 5-es, 2007 | 3177 | 2007 |
| Cost-effective outbreak detection in networks J Leskovec, A Krause, C Guestrin, C Faloutsos, J VanBriesen, N Glance Proceedings of the 13th ACM SIGKDD international conference on Knowledge …, 2007 | 3074 | 2007 |
| On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021 | 2678 | 2021 |
| Mining of massive data sets J Leskovec, A Rajaraman, JD Ullman Cambridge university press, 2020 | 2661 | 2020 |
| Defining and evaluating network communities based on ground-truth J Yang, J Leskovec Proceedings of the ACM SIGKDD Workshop on Mining Data Semantics, 1-8, 2012 | 2473 | 2012 |
| Learning to discover social circles in ego networks J Leskovec, J Mcauley Advances in neural information processing systems 25, 2012 | 2454 | 2012 |
| Representation learning on graphs: Methods and applications WL Hamilton, R Ying, J Leskovec arXiv preprint arXiv:1709.05584, 2017 | 2317 | 2017 |
| Community structure in large networks: Natural cluster sizes and the absence of large well-defined clusters J Leskovec, KJ Lang, A Dasgupta, MW Mahoney Internet Mathematics 6 (1), 29-123, 2009 | 2314 | 2009 |
| Open graph benchmark: Datasets for machine learning on graphs W Hu, M Fey, M Zitnik, Y Dong, H Ren, B Liu, M Catasta, J Leskovec Advances in neural information processing systems 33, 22118-22133, 2020 | 2214 | 2020 |
| Hidden factors and hidden topics: understanding rating dimensions with review text J McAuley, J Leskovec Proceedings of the 7th ACM conference on Recommender systems, 165-172, 2013 | 2090 | 2013 |
| Meme-tracking and the dynamics of the news cycle J Leskovec, L Backstrom, J Kleinberg Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009 | 2058 | 2009 |
| Predicting positive and negative links in online social networks J Leskovec, D Huttenlocher, J Kleinberg Proceedings of the 19th international conference on World wide web, 641-650, 2010 | 1924 | 2010 |
Rex (Zhitao) YingYale UniversityE-mail megerősítve itt: yale.edu
