Xiaowen Dong

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 100

Top Venues

Publications

Shuo Tang, Rui Ye, Chenxin Xu, Xiaowen Dong, Siheng Chen, Yanfeng Wang
Decentralized and Lifelong-Adaptive Multi-Agent Collaborative Learning. CoRR (2024)
Zexi Liu, Bohan Tang, Ziyuan Ye, Xiaowen Dong, Siheng Chen, Yanfeng Wang
Hypergraph Transformer for Semi-Supervised Classification. ICASSP (2024)
Fernando Moreno-Pino, Alvaro Arroyo, Harrison Waldon, Xiaowen Dong, Álvaro Cartea
Rough Transformers: Lightweight Continuous-Time Sequence Modelling with Path Signatures. CoRR (2024)
Baskaran Sripathmanathan, Xiaowen Dong, Michael M. Bronstein
On the Impact of Sample Size in Reconstructing Noisy Graph Signals: A Theoretical Characterisation. CoRR (2024)
Déborah Sulem, Henry Kenlay, Mihai Cucuringu, Xiaowen Dong
Graph similarity learning for change-point detection in dynamic networks. Mach. Learn. 113 (1) (2024)
Bohan Tang, Zexi Liu, Keyue Jiang, Siheng Chen, Xiaowen Dong
Hypergraph Node Classification With Graph Neural Networks. CoRR (2024)
Isabelle Lorge, Li Zhang, Xiaowen Dong, Janet B. Pierrehumbert
STEntConv: Predicting Disagreement with Stance Detection and a Signed Graph Convolutional Network. CoRR (2024)
Huidong Liang, Xingchen Wan, Xiaowen Dong
Bayesian Optimization of Functions over Node Subsets in Graphs. CoRR (2024)
Jacob Bamberger, Federico Barbero, Xiaowen Dong, Michael M. Bronstein
Bundle Neural Networks for message diffusion on graphs. CoRR (2024)
Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin
A Characterization Theorem for Equivariant Networks with Point-wise Activations. CoRR (2024)
Fernando Moreno-Pino, Alvaro Arroyo, Harrison Waldon, Xiaowen Dong, Álvaro Cartea
Rough Transformers for Continuous and Efficient Time-Series Modelling. CoRR (2024)
Yuqi Nie, Yaxuan Kong, Xiaowen Dong, John M. Mulvey, H. Vincent Poor, Qingsong Wen, Stefan Zohren
A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges. CoRR (2024)
Isabelle Lorge, Li Zhang, Xiaowen Dong, Janet B. Pierrehumbert
STEntConv: Predicting Disagreement between Reddit Users with Stance Detection and a Signed Graph Convolutional Network. LREC/COLING (2024)
Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin
A Characterization Theorem for Equivariant Networks with Point-wise Activations. ICLR (2024)
Yan Leng, Xiaowen Dong, Esteban Moro, Alex Pentland
Long-Range Social Influence in Phone Communication Networks on Offline Adoption Decisions. Inf. Syst. Res. 35 (1) (2024)
Mihai Cucuringu, Xiaowen Dong, Ning Zhang
Maximum Likelihood Estimation on Stochastic Blockmodels for Directed Graph Clustering. CoRR (2024)
Bohan Tang, Siheng Chen, Xiaowen Dong
Hypergraph-Mlp: Learning on Hypergraphs Without Message Passing. ICASSP (2024)
Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin
Separation Power of Equivariant Neural Networks. CoRR (2024)
Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A. Osborne, Xiaowen Dong
Bayesian Optimisation of Functions on Graphs. CoRR (2023)
Baskaran Sripathmanathan, Xiaowen Dong, Michael M. Bronstein
On the Impact of Sample Size in Reconstructing Graph Signals. CoRR (2023)
Zexi Liu, Bohan Tang, Ziyuan Ye, Xiaowen Dong, Siheng Chen, Yanfeng Wang
Hypergraph Transformer for Semi-Supervised Classification. CoRR (2023)
Xingyue Pu, Stephen J. Roberts, Xiaowen Dong, Stefan Zohren
Network Momentum across Asset Classes. CoRR (2023)
Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni
DRew: Dynamically Rewired Message Passing with Delay. ICML (2023)
Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong
Graph Classification Gaussian Processes via Spectral Features. CoRR (2023)
Bohan Tang, Siheng Chen, Xiaowen Dong
Hypergraph Structure Inference From Data Under Smoothness Prior. CoRR (2023)
Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong, Marya Bazzi, Mihai Cucuringu
Local2Global: a distributed approach for scaling representation learning on graphs. Mach. Learn. 112 (5) (2023)
Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong
Graph classification Gaussian processes via spectral features. UAI (2023)
Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ismael Morales, Ingmar Posner, Xiaowen Dong
Gromov-Hausdorff Distances for Comparing Product Manifolds of Model Spaces. CoRR (2023)
Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ismael Morales, Ingmar Posner, Xiaowen Dong
Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization. CoRR (2023)
Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni
DRew: Dynamically Rewired Message Passing with Delay. CoRR (2023)
Pierre Osselin, Henry Kenlay, Xiaowen Dong
Structure-aware robustness certificates for graph classification. UAI (2023)
Chao Zhang, Xingyue Pu, Mihai Cucuringu, Xiaowen Dong
Graph Neural Networks for Forecasting Multivariate Realized Volatility with Spillover Effects. CoRR (2023)
Pierre Osselin, Henry Kenlay, Xiaowen Dong
Structure-Aware Robustness Certificates for Graph Classification. CoRR (2023)
Xingyue Pu, Stefan Zohren, Stephen J. Roberts, Xiaowen Dong
Learning to Learn Financial Networks for Optimising Momentum Strategies. CoRR (2023)
Bohan Tang, Siheng Chen, Xiaowen Dong
Learning Hypergraphs From Signals With Dual Smoothness Prior. ICASSP (2023)
Yin-Cong Zhi, Yin Cheng Ng, Xiaowen Dong
Gaussian Processes on Graphs Via Spectral Kernel Learning. IEEE Trans. Signal Inf. Process. over Networks 9 (2023)
Bohan Tang, Siheng Chen, Xiaowen Dong
Hypergraph-MLP: Learning on Hypergraphs without Message Passing. CoRR (2023)
Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ismael Morales, Ingmar Posner, Xiaowen Dong
Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization. NeurIPS (2023)
Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A. Osborne, Xiaowen Dong
Bayesian Optimisation of Functions on Graphs. NeurIPS (2023)
Emanuele Rossi, Federico Monti, Yan Leng, Michael M. Bronstein, Xiaowen Dong
Learning to Infer Structures of Network Games. ICML (2022)
Yin-Cong Zhi, Felix L. Opolka, Yin Cheng Ng, Pietro Liò, Xiaowen Dong
Transductive Kernels for Gaussian Processes on Graphs. CoRR (2022)
Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
Understanding over-squashing and bottlenecks on graphs via curvature. ICLR (2022)
Valentin Hofmann, Xiaowen Dong, Janet B. Pierrehumbert, Hinrich Schütze
Modeling Ideological Salience and Framing in Polarized Online Groups with Graph Neural Networks and Structured Sparsity. NAACL-HLT (Findings) (2022)
Déborah Sulem, Henry Kenlay, Mihai Cucuringu, Xiaowen Dong
Graph similarity learning for change-point detection in dynamic networks. CoRR (2022)
Dragos Gorduza, Xiaowen Dong, Stefan Zohren
Understanding stock market instability via graph auto-encoders. CoRR (2022)
Bohan Tang, Siheng Chen, Xiaowen Dong
Learning Hypergraphs From Signals With Dual Smoothness Prior. CoRR (2022)
Diego Granziol, Binxin Ru, Xiaowen Dong, Stefan Zohren, Michael A. Osborne, Stephen J. Roberts
Maximum Entropy Approach to Massive Graph Spectrum Learning with Applications. Algorithms 15 (6) (2022)
Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong
Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets. AISTATS (2022)
Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
On the Unreasonable Effectiveness of Feature Propagation in Learning on Graphs With Missing Node Features. LoG (2022)
Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong, Marya Bazzi, Mihai Cucuringu
Local2Global: A distributed approach for scaling representation learning on graphs. CoRR (2022)
Emanuele Rossi, Federico Monti, Yan Leng, Michael M. Bronstein, Xiaowen Dong
Learning to Infer Structures of Network Games. CoRR (2022)
Enpei Zhang, Shuo Tang, Xiaowen Dong, Siheng Chen, Yanfeng Wang
Unrolled Graph Learning for Multi-Agent Collaboration. CoRR (2022)
Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
Understanding over-squashing and bottlenecks on graphs via curvature. CoRR (2021)
Mahmoud Ramezani Mayiami, Mohammad Hajimirsadeghi, Karl Skretting, Xiaowen Dong, Rick S. Blum, H. Vincent Poor
Bayesian Topology Learning and noise removal from network data. Discov. Internet Things 1 (1) (2021)
Xingyue Pu, Tianyue Cao, Xiaoyun Zhang, Xiaowen Dong, Siheng Chen
Learning to Learn Graph Topologies. NeurIPS (2021)
Xingchen Wan, Henry Kenlay, Binxin Ru, Arno Blaas, Michael A. Osborne, Xiaowen Dong
Adversarial Attacks on Graph Classification via Bayesian Optimisation. CoRR (2021)
Henry Kenlay, Dorina Thanou, Xiaowen Dong
On The Stability of Graph Convolutional Neural Networks Under Edge Rewiring. ICASSP (2021)
Benjamin Paul Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael M. Bronstein
Beltrami Flow and Neural Diffusion on Graphs. CoRR (2021)
Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features. CoRR (2021)
Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong
Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets. CoRR (2021)
Ben Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael M. Bronstein
Beltrami Flow and Neural Diffusion on Graphs. NeurIPS (2021)
Xingyue Pu, Tianyue Cao, Xiaoyun Zhang, Xiaowen Dong, Siheng Chen
Learning to Learn Graph Topologies. CoRR (2021)
Henry Kenlay, Dorina Thanou, Xiaowen Dong
Interpretable Stability Bounds for Spectral Graph Filters. ICML (2021)
Henry Kenlay, Dorina Thanou, Xiaowen Dong
Interpretable Stability Bounds for Spectral Graph Filters. CoRR (2021)
Mahmoud Ramezani-Mayiami, Mohammad Hajimirsadeghi, Karl Skretting, Xiaowen Dong, Rick S. Blum, H. Vincent Poor
Correction to: Bayesian Topology Learning and noise removal from network data. Discov. Internet Things 1 (1) (2021)
Xingchen Wan, Henry Kenlay, Robin Ru, Arno Blaas, Michael A. Osborne, Xiaowen Dong
Adversarial Attacks on Graph Classifiers via Bayesian Optimisation. NeurIPS (2021)
Xingyue Pu, Siu Lun Chau, Xiaowen Dong, Dino Sejdinovic
Kernel-Based Graph Learning From Smooth Signals: A Functional Viewpoint. IEEE Trans. Signal Inf. Process. over Networks 7 (2021)
Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong, Marya Bazzi, Mihai Cucuringu
Local2Global: Scaling global representation learning on graphs via local training. CoRR (2021)
Bin Xin Ru, Xingchen Wan, Xiaowen Dong, Michael A. Osborne
Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels. ICLR (2021)
Yan Leng, Xiaowen Dong, Junfeng Wu, Alex Pentland
Learning Quadratic Games on Networks. ICML (2020)
Oliver Gardiner, Xiaowen Dong
Mobility Networks for Predicting Gentrification. COMPLEX NETWORKS (2) (2020)
Xingchen Wan, Jie Yang, Slavi Marinov, Jan-Peter Calliess, Stefan Zohren, Xiaowen Dong
Sentiment Diffusion in Financial News Networks and Associated Market Movements. CoRR (2020)
Bin Xin Ru, Xingchen Wan, Xiaowen Dong, Michael A. Osborne
Neural Architecture Search using Bayesian Optimisation with Weisfeiler-Lehman Kernel. CoRR (2020)
Yin-Cong Zhi, Yin Cheng Ng, Xiaowen Dong
Gaussian Processes on Graphs via Spectral Kernel Learning. CoRR (2020)
Xiaowen Dong, Dorina Thanou, Laura Toni, Michael M. Bronstein, Pascal Frossard
Graph signal processing for machine learning: A review and new perspectives. CoRR (2020)
Xiaowen Dong, Alfredo Jose Morales, Eaman Jahani, Esteban Moro, Bruno Lepri, Burçin Bozkaya, Carlos Sarraute, Yaneer Bar-Yam, Alex Pentland
Segregated interactions in urban and online space. EPJ Data Sci. 9 (1) (2020)
Henry Kenlay, Dorina Thanou, Xiaowen Dong
On The Stability of Polynomial Spectral Graph Filters. ICASSP (2020)
Xiaowen Dong, Dorina Thanou, Laura Toni, Michael M. Bronstein, Pascal Frossard
Graph Signal Processing for Machine Learning: A Review and New Perspectives. IEEE Signal Process. Mag. 37 (6) (2020)
Kaige Yang, Laura Toni, Xiaowen Dong
Laplacian-Regularized Graph Bandits: Algorithms and Theoretical Analysis. AISTATS (2020)
Xingyue Pu, Siu Lun Chau, Xiaowen Dong, Dino Sejdinovic
Kernel-based Graph Learning from Smooth Signals: A Functional Viewpoint. CoRR (2020)
Henry Kenlay, Dorina Thanou, Xiaowen Dong
On the Stability of Graph Convolutional Neural Networks under Edge Rewiring. CoRR (2020)
Kaige Yang, Xiaowen Dong, Laura Toni
Laplacian-regularized graph bandits: Algorithms and theoretical analysis. CoRR (2019)
Diego Granziol, Robin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
A Maximum Entropy approach to Massive Graph Spectra. CoRR (2019)
Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. Entropy 21 (6) (2019)
Xiaowen Dong, Dorina Thanou, Michael G. Rabbat, Pascal Frossard
Learning Graphs From Data: A Signal Representation Perspective. IEEE Signal Process. Mag. 36 (3) (2019)
Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. CoRR (2019)
Kaige Yang, Xiaowen Dong, Laura Toni
Error Analysis on Graph Laplacian Regularized Estimator. CoRR (2019)
Xiaowen Dong, Alfredo Jose Morales, Eaman Jahani, Esteban Moro, Bruno Lepri, Burçin Bozkaya, Carlos Sarraute, Yaneer Bar-Yam, Alex Pentland
Segregated interactions in urban and online spaces. CoRR (2019)
Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
Entropic Spectral Learning in Large Scale Networks. CoRR (2018)
Albert Ali Salah, Alex Pentland, Bruno Lepri, Emmanuel Letouzé, Patrick Vinck, Yves-Alexandre de Montjoye, Xiaowen Dong, Özge Dagdelen
Data for Refugees: The D4R Challenge on Mobility of Syrian Refugees in Turkey. CoRR (2018)
Erdem Kaya, Xiaowen Dong, Yoshihiko Suhara, Selim Balcisoy, Burçin Bozkaya, Alex 'Sandy' Pentland
Behavioral attributes and financial churn prediction. EPJ Data Sci. 7 (1) (2018)
Xiaowen Dong, Yoshihiko Suhara, Burçin Bozkaya, Vivek K. Singh, Bruno Lepri, Alex 'Sandy' Pentland
Social Bridges in Urban Purchase Behavior. ACM Trans. Intell. Syst. Technol. 9 (3) (2018)
Yan Leng, Xiaowen Dong, Alex Pentland
Learning Quadratic Games on Networks. CoRR (2018)
Xiaowen Dong, Dorina Thanou, Michael G. Rabbat, Pascal Frossard
Learning Graphs from Data: A Signal Representation Perspective. CoRR (2018)
Xiaowen Dong, Joachim Meyer, Erez Shmueli, Burçin Bozkaya, Alex Pentland
Methods for quantifying effects of social unrest using credit card transaction data. EPJ Data Sci. 7 (1) (2018)
Dorina Thanou, Xiaowen Dong, Daniel Kressner, Pascal Frossard
Learning Heat Diffusion Graphs. IEEE Trans. Signal Inf. Process. over Networks 3 (3) (2017)
Dorina Thanou, Xiaowen Dong, Daniel Kressner, Pascal Frossard
Learning heat diffusion graphs. CoRR (2016)
Renata Khasanova, Xiaowen Dong, Pascal Frossard
Multi-modal image retrieval with random walk on multi-layer graphs. CoRR (2016)
Renata Khasanova, Xiaowen Dong, Pascal Frossard
Multi-modal Image Retrieval with Random Walk on Multi-layer Graphs. ISM (2016)
Xiaowen Dong, Dorina Thanou, Pascal Frossard, Pierre Vandergheynst
Learning Laplacian Matrix in Smooth Graph Signal Representations. IEEE Trans. Signal Process. 64 (23) (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Xiaowen Dong