| Learning Laplacian matrix in smooth graph signal representations X Dong, D Thanou, P Frossard, P Vandergheynst IEEE Transactions on Signal Processing 64 (23), 6160-6173, 2016 | 668 | 2016 |
| Learning graphs from data: A signal representation perspective X Dong, D Thanou, M Rabbat, P Frossard IEEE Signal Processing Magazine 36 (3), 44-63, 2019 | 429 | 2019 |
| Understanding over-squashing and bottlenecks on graphs via curvature J Topping, F Di Giovanni, BP Chamberlain, X Dong, MM Bronstein International Conference on Learning Representations (ICLR), 2022 | 371 | 2022 |
| Clustering on multi-layer graphs via subspace analysis on Grassmann manifolds X Dong, P Frossard, P Vandergheynst, N Nefedov IEEE Transactions on Signal Processing 62 (4), 905-918, 2014 | 236 | 2014 |
| Clustering on multi-layer graphs via subspace analysis on Grassmann manifolds X Dong, P Frossard, P Vandergheynst, N Nefedov IEEE Global Conference on Signal and Information Processing (GlobalSIP), 993-996, 2013 | 236 | 2013 |
| Learning heat diffusion graphs D Thanou, X Dong, D Kressner, P Frossard IEEE Transactions on Signal and Information Processing over Networks 3 (3 …, 2017 | 188 | 2017 |
| Clustering with multi-layer graphs: A spectral perspective X Dong, P Frossard, P Vandergheynst, N Nefedov IEEE Transactions on Signal Processing 60 (11), 5820-5831, 2012 | 184 | 2012 |
| Graph signal processing for machine learning: A review and new perspectives X Dong, D Thanou, L Toni, M Bronstein, P Frossard IEEE Signal Processing Magazine 37 (6), 117-127, 2020 | 166 | 2020 |
| Multiscale event detection in social media X Dong, D Mavroeidis, F Calabrese, P Frossard Data Mining and Knowledge Discovery 29, 1374-1405, 2015 | 155 | 2015 |
| Mobility patterns are associated with experienced income segregation in large US cities E Moro, D Calacci, X Dong, A Pentland Nature communications 12 (1), 4633, 2021 | 151 | 2021 |
| Interpretable neural architecture search via Bayesian optimisation with Weisfeiler-Lehman kernels B Ru, X Wan, X Dong, MA Osborne International Conference on Learning Representations (ICLR), 2021 | 109 | 2021 |
| On the unreasonable effectiveness of feature propagation in learning on graphs with missing node features E Rossi, H Kenlay, MI Gorinova, BP Chamberlain, X Dong, MM Bronstein Learning on Graphs Conference (LoG), 11:1-11:16, 2022 | 75 | 2022 |
| Laplacian matrix learning for smooth graph signal representation X Dong, D Thanou, P Frossard, P Vandergheynst IEEE international conference on Acoustics, Speech and Signal Processing …, 2015 | 73 | 2015 |
| Beltrami flow and neural diffusion on graphs B Chamberlain, J Rowbottom, D Eynard, F Di Giovanni, X Dong, ... Conference on Neural Information Processing Systems (NeurIPS), 1594-1609, 2021 | 69 | 2021 |
| Sentiment correlation in financial news networks and associated market movements X Wan, J Yang, S Marinov, JP Calliess, S Zohren, X Dong Scientific Reports 11 (1), 1-12, 2021 | 62 | 2021 |
| Introduction to the Data for Refugees Challenge on mobility of Syrian refugees in Turkey AA Salah, A Pentland, B Lepri, E Letouzé, YA de Montjoye, X Dong, ... Guide to Mobile Data Analytics in Refugee Scenarios: The 'Data for Refugees …, 2019 | 59* | 2019 |
| Segregated interactions in urban and online space X Dong, AJ Morales, E Jahani, E Moro, B Lepri, B Bozkaya, C Sarraute, ... EPJ Data Science 9 (1), 20, 2020 | 56 | 2020 |
| Learning of structured graph dictionaries X Zhang, X Dong, P Frossard IEEE International Conference on Acoustics, Speech and Signal Processing …, 2012 | 55 | 2012 |
| Segregation and polarization in urban areas AJ Morales, X Dong, Y Bar-Yam, A Pentland Royal Society Open Science 6 (10), 190573, 2019 | 50 | 2019 |
| Behavioral attributes and financial churn prediction E Kaya, X Dong, Y Suhara, S Balcisoy, B Bozkaya EPJ Data Science 7 (1), 41, 2018 | 49 | 2018 |
Pascal FrossardEcole Polytechnique Fédérale de Lausanne, EPFL在 epfl.ch 的电子邮件经过验证
