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Xiaowen Dong
Xiaowen Dong
University of Oxford
Подтвержден адрес электронной почты в домене robots.ox.ac.uk - Главная страница
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Процитировано
Процитировано
Год
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
7292016
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
5122022
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
4812019
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
2542014
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
2542013
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
2152021
Learning heat diffusion graphs
D Thanou, X Dong, D Kressner, P Frossard
IEEE Transactions on Signal and Information Processing over Networks 3 (3 …, 2017
2112017
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
2042020
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
1932012
Multiscale event detection in social media
X Dong, D Mavroeidis, F Calabrese, P Frossard
Data Mining and Knowledge Discovery 29, 1374-1405, 2015
1592015
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
1282021
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
1092022
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
922021
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), 3062, 2021
752021
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
752015
DRew: Dynamically rewired message passing with delay
B Gutteridge, X Dong, MM Bronstein, F Di Giovanni
International Conference on Machine Learning (ICML), 12252-12267, 2023
722023
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
672020
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
61*2019
Segregation and polarization in urban areas
AJ Morales, X Dong, Y Bar-Yam, A Pentland
Royal Society Open Science 6 (10), 190573, 2019
602019
Learning of structured graph dictionaries
X Zhang, X Dong, P Frossard
IEEE International Conference on Acoustics, Speech and Signal Processing …, 2012
572012
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Статьи 1–20