Xiaowen Dong - RankMe

153 papers A* 19A 5C 1Misc 9Journal 108Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Bipartite Graph Approach to U.S.-China Cross-Market Return Forecasting. CoRR Jing Liu, Maria Grith, Xiaowen Dong, Mihai Cucuringu
2026	J	`jnl`	A Survey on Over-smoothing and Over-squashing: Unified Propagation Perspectives on Graph Neural Networks and Transformers. Trans. Mach. Learn. Res. Alvaro Arroyo, Federico Barbero, Hugh Blayney, Michael M. Bronstein, Xiaowen Dong, Pietro Lio, Razvan Pascanu, Pierre Vandergheynst
2026	J	`jnl`	Can Graph Foundation Models Generalize Over Architecture? CoRR Benjamin Gutteridge, Michael M. Bronstein, Xiaowen Dong
2026	J	`jnl`	Data-Driven Graph Filters via Adaptive Spectral Shaping. CoRR Dylan Sandfelder, Mihai Cucuringu, Xiaowen Dong
2025	J	`jnl`	Attention Sinks and Compression Valleys in LLMs are Two Sides of the Same Coin. CoRR Enrique Queipo-de-Llano, Alvaro Arroyo, Federico Barbero, Xiaowen Dong, Michael M. Bronstein, Yann LeCun, Ravid Shwartz-Ziv
2025	A*	`conf`	Bundle Neural Network for message diffusion on graphs. ICLR Jacob Bamberger, Federico Barbero, Xiaowen Dong, Michael M. Bronstein
2025	J	`jnl`	Bures-Wasserstein Flow Matching for Graph Generation. CoRR Keyue Jiang, Jiahao Cui, Xiaowen Dong, Laura Toni
2025	J	`jnl`	GNNs as Predictors of Agentic Workflow Performances. CoRR Yuanshuo Zhang, Yuchen Hou, Bohan Tang, Shuo Chen, Muhan Zhang, Xiaowen Dong, Siheng Chen
2025	J	`jnl`	Graph and Simplicial Complex Prediction Gaussian Process via the Hodgelet Representations. CoRR Mathieu Alain, So Takao, Xiaowen Dong, Bastian Rieck, Emmanuel Noutahi
2025	A	`conf`	Heterogeneous Graph Structure Learning through the Lens of Data-generating Processes. AISTATS Keyue Jiang, Bohan Tang, Xiaowen Dong, Laura Toni
2025	J	`jnl`	Heterogeneous Graph Structure Learning through the Lens of Data-generating Processes. CoRR Keyue Jiang, Bohan Tang, Xiaowen Dong, Laura Toni
2025	J	`jnl`	Judge a Book by its Cover: Investigating Multi-Modal LLMs for Multi-Page Handwritten Document Transcription. CoRR Benjamin Gutteridge, Matthew Thomas Jackson, Toni Kukurin, Xiaowen Dong
2025	J	`jnl`	LGDC: Latent Graph Diffusion via Spectrum-Preserving Coarsening. CoRR Nagham Osman, Keyue Jiang, Davide Buffelli, Xiaowen Dong, Laura Toni
2025	—	`conf`	Natural Evolutionary Search meets Probabilistic Numerics. ProbNum Pierre Osselin, Masaki Adachi, Xiaowen Dong, Michael A. Osborne
2025	J	`jnl`	Natural Evolutionary Search meets Probabilistic Numerics. CoRR Pierre Osselin, Masaki Adachi, Xiaowen Dong, Michael A. Osborne
2025	A*	`conf`	Neural Spacetimes for DAG Representation Learning. ICLR Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T. Law, Xiaowen Dong, Michael M. Bronstein
2025	A*	`conf`	On Measuring Long-Range Interactions in Graph Neural Networks. ICML Jacob Bamberger, Benjamin Gutteridge, Scott le Roux, Michael M. Bronstein, Xiaowen Dong
2025	J	`jnl`	On Measuring Long-Range Interactions in Graph Neural Networks. CoRR Jacob Bamberger, Benjamin Gutteridge, Scott le Roux, Michael M. Bronstein, Xiaowen Dong
2025	J	`jnl`	On Vanishing Gradients, Over-Smoothing, and Over-Squashing in GNNs: Bridging Recurrent and Graph Learning. CoRR Alvaro Arroyo, Alessio Gravina, Benjamin Gutteridge, Federico Barbero, Claudio Gallicchio, Xiaowen Dong, Michael M. Bronstein, Pierre Vandergheynst
2025	—	`conf`	On the Impact of Downstream Tasks on Sampling and Reconstructing Noisy Graph Signals. CAMSAP Baskaran Sripathmanathan, Xiaowen Dong, Michael M. Bronstein
2025	J	`jnl`	On the Impact of Downstream Tasks on Sampling and Reconstructing Noisy Graph Signals. CoRR Baskaran Sripathmanathan, Xiaowen Dong, Michael M. Bronstein
2025	J	`jnl`	On the Importance of Task Complexity in Evaluating LLM-Based Multi-Agent Systems. CoRR Bohan Tang, Huidong Liang, Keyue Jiang, Xiaowen Dong
2025	J	`jnl`	On the Stability of Graph Convolutional Neural Networks: A Probabilistic Perspective. CoRR Ning Zhang, Henry Kenlay, Li Zhang, Mihai Cucuringu, Xiaowen Dong
2025	J	`jnl`	Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks. CoRR Ali Hariri, Alvaro Arroyo, Alessio Gravina, Moshe Eliasof, Carola-Bibiane Schönlieb, Davide Bacciu, Kamyar Azizzadenesheli, Xiaowen Dong, Pierre Vandergheynst
2025	A*	`conf`	Separation Power of Equivariant Neural Networks. ICLR Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin
2025	—	`conf`	Synthesizing Post-Training Data for LLMs through Multi-Agent Simulation. ACL (1) Shuo Tang, Xianghe Pang, Zexi Liu, Bohan Tang, Rui Ye, Tian Jin, Xiaowen Dong, Yanfeng Wang, Siheng Chen
2025	J	`jnl`	Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement. CoRR Huidong Liang, Haitz Sáez de Ocáriz Borde, Baskaran Sripathmanathan, Michael M. Bronstein, Xiaowen Dong
2025	A*	`conf`	Training-Free Message Passing for Learning on Hypergraphs. ICLR Bohan Tang, Zexi Liu, Keyue Jiang, Siheng Chen, Xiaowen Dong
2025	J	`jnl`	Understanding stock market instability via graph auto-encoders. EPJ Data Sci. Dragos Gorduza, Stefan Zohren, Xiaowen Dong
2025	J	`jnl`	gLSTM: Mitigating Over-Squashing by Increasing Storage Capacity. CoRR Hugh Blayney, Alvaro Arroyo, Xiaowen Dong, Michael M. Bronstein
2024	A*	`conf`	A Characterization Theorem for Equivariant Networks with Point-wise Activations. ICLR Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin
2024	J	`jnl`	A Characterization Theorem for Equivariant Networks with Point-wise Activations. CoRR Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin
2024	J	`jnl`	A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges. CoRR Yuqi Nie, Yaxuan Kong, Xiaowen Dong, John M. Mulvey, H. Vincent Poor, Qingsong Wen, Stefan Zohren
2024	J	`jnl`	Are We There Yet? Revealing the Risks of Utilizing Large Language Models in Scholarly Peer Review. CoRR Rui Ye, Xianghe Pang, Jingyi Chai, Jiaao Chen, Zhenfei Yin, Zhen Xiang, Xiaowen Dong, Jing Shao, Siheng Chen
2024	A*	`conf`	Bayesian Optimization of Functions over Node Subsets in Graphs. NeurIPS Huidong Liang, Xingchen Wan, Xiaowen Dong
2024	J	`jnl`	Bayesian Optimization of Functions over Node Subsets in Graphs. CoRR Huidong Liang, Xingchen Wan, Xiaowen Dong
2024	J	`jnl`	Bundle Neural Networks for message diffusion on graphs. CoRR Jacob Bamberger, Federico Barbero, Xiaowen Dong, Michael M. Bronstein
2024	J	`jnl`	Decentralized and Lifelong-Adaptive Multi-Agent Collaborative Learning. CoRR Shuo Tang, Rui Ye, Chenxin Xu, Xiaowen Dong, Siheng Chen, Yanfeng Wang
2024	—	`conf`	Extracting Alpha from Financial Analyst Networks. ICAIF Dragos Gorduza, Yaxuan Kong, Xiaowen Dong, Stefan Zohren
2024	J	`jnl`	Graph Classification Gaussian Processes via Hodgelet Spectral Features. CoRR Mathieu Alain, So Takao, Xiaowen Dong, Bastian Rieck, Emmanuel Noutahi
2024	J	`jnl`	Graph similarity learning for change-point detection in dynamic networks. Mach. Learn. Déborah Sulem, Henry Kenlay, Mihai Cucuringu, Xiaowen Dong
2024	J	`jnl`	Hypergraph Node Classification With Graph Neural Networks. CoRR Bohan Tang, Zexi Liu, Keyue Jiang, Siheng Chen, Xiaowen Dong
2024	Misc	`conf`	Hypergraph Transformer for Semi-Supervised Classification. ICASSP Zexi Liu, Bohan Tang, Ziyuan Ye, Xiaowen Dong, Siheng Chen, Yanfeng Wang
2024	Misc	`conf`	Hypergraph-Mlp: Learning on Hypergraphs Without Message Passing. ICASSP Bohan Tang, Siheng Chen, Xiaowen Dong
2024	J	`jnl`	Long-Range Social Influence in Phone Communication Networks on Offline Adoption Decisions. Inf. Syst. Res. Yan Leng, Xiaowen Dong, Esteban Moro, Alex Pentland
2024	J	`jnl`	Maximum Likelihood Estimation on Stochastic Blockmodels for Directed Graph Clustering. CoRR Mihai Cucuringu, Xiaowen Dong, Ning Zhang
2024	J	`jnl`	Neural Spacetimes for DAG Representation Learning. CoRR Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T. Law, Xiaowen Dong, Michael M. Bronstein
2024	J	`jnl`	On the Impact of Sample Size in Reconstructing Noisy Graph Signals: A Theoretical Characterisation. CoRR Baskaran Sripathmanathan, Xiaowen Dong, Michael M. Bronstein
2024	J	`jnl`	Rough Transformers for Continuous and Efficient Time-Series Modelling. CoRR Fernando Moreno-Pino, Alvaro Arroyo, Harrison Waldon, Xiaowen Dong, Álvaro Cartea
2024	J	`jnl`	Rough Transformers: Lightweight Continuous-Time Sequence Modelling with Path Signatures. CoRR Fernando Moreno-Pino, Alvaro Arroyo, Harrison Waldon, Xiaowen Dong, Álvaro Cartea
2024	A*	`conf`	Rough Transformers: Lightweight and Continuous Time Series Modelling through Signature Patching. NeurIPS Fernando Moreno-Pino, Alvaro Arroyo, Harrison Waldon, Xiaowen Dong, Álvaro Cartea
2024	—	`conf`	STEntConv: Predicting Disagreement between Reddit Users with Stance Detection and a Signed Graph Convolutional Network. LREC/COLING Isabelle Lorge, Li Zhang, Xiaowen Dong, Janet B. Pierrehumbert
2024	J	`jnl`	STEntConv: Predicting Disagreement with Stance Detection and a Signed Graph Convolutional Network. CoRR Isabelle Lorge, Li Zhang, Xiaowen Dong, Janet B. Pierrehumbert
2024	J	`jnl`	Scalable Message Passing Neural Networks: No Need for Attention in Large Graph Representation Learning. CoRR Haitz Sáez de Ocáriz Borde, Artem Lukoianov, Anastasis Kratsios, Michael M. Bronstein, Xiaowen Dong
2024	J	`jnl`	Separation Power of Equivariant Neural Networks. CoRR Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin
2024	J	`jnl`	Synthesizing Post-Training Data for LLMs through Multi-Agent Simulation. CoRR Shuo Tang, Xianghe Pang, Zexi Liu, Bohan Tang, Rui Ye, Xiaowen Dong, Yanfeng Wang, Siheng Chen
2023	A*	`conf`	Bayesian Optimisation of Functions on Graphs. NeurIPS Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A. Osborne, Xiaowen Dong
2023	J	`jnl`	Bayesian Optimisation of Functions on Graphs. CoRR Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A. Osborne, Xiaowen Dong
2023	A*	`conf`	DRew: Dynamically Rewired Message Passing with Delay. ICML Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni
2023	J	`jnl`	DRew: Dynamically Rewired Message Passing with Delay. CoRR Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni
2023	J	`jnl`	Gaussian Processes on Graphs Via Spectral Kernel Learning. IEEE Trans. Signal Inf. Process. over Networks Yin-Cong Zhi, Yin Cheng Ng, Xiaowen Dong
2023	J	`jnl`	Graph Classification Gaussian Processes via Spectral Features. CoRR Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong
2023	J	`jnl`	Graph Neural Networks for Forecasting Multivariate Realized Volatility with Spillover Effects. CoRR Chao Zhang, Xingyue Pu, Mihai Cucuringu, Xiaowen Dong
2023	A	`conf`	Graph classification Gaussian processes via spectral features. UAI Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong
2023	J	`jnl`	Gromov-Hausdorff Distances for Comparing Product Manifolds of Model Spaces. CoRR Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ismael Morales, Ingmar Posner, Xiaowen Dong
2023	J	`jnl`	Hypergraph Structure Inference From Data Under Smoothness Prior. CoRR Bohan Tang, Siheng Chen, Xiaowen Dong
2023	J	`jnl`	Hypergraph Transformer for Semi-Supervised Classification. CoRR Zexi Liu, Bohan Tang, Ziyuan Ye, Xiaowen Dong, Siheng Chen, Yanfeng Wang
2023	J	`jnl`	Hypergraph-MLP: Learning on Hypergraphs without Message Passing. CoRR Bohan Tang, Siheng Chen, Xiaowen Dong
2023	Misc	`conf`	Learning Hypergraphs From Signals With Dual Smoothness Prior. ICASSP Bohan Tang, Siheng Chen, Xiaowen Dong
2023	J	`jnl`	Learning to Learn Financial Networks for Optimising Momentum Strategies. CoRR Xingyue Pu, Stefan Zohren, Stephen J. Roberts, Xiaowen Dong
2023	J	`jnl`	Local2Global: a distributed approach for scaling representation learning on graphs. Mach. Learn. Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong, Marya Bazzi, Mihai Cucuringu
2023	J	`jnl`	Network Momentum across Asset Classes. CoRR Xingyue Pu, Stephen J. Roberts, Xiaowen Dong, Stefan Zohren
2023	A*	`conf`	Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization. NeurIPS Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ismael Morales, Ingmar Posner, Xiaowen Dong
2023	J	`jnl`	Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization. CoRR Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ismael Morales, Ingmar Posner, Xiaowen Dong
2023	J	`jnl`	On the Impact of Sample Size in Reconstructing Graph Signals. CoRR Baskaran Sripathmanathan, Xiaowen Dong, Michael M. Bronstein
2023	J	`jnl`	Structure-Aware Robustness Certificates for Graph Classification. CoRR Pierre Osselin, Henry Kenlay, Xiaowen Dong
2023	A	`conf`	Structure-aware robustness certificates for graph classification. UAI Pierre Osselin, Henry Kenlay, Xiaowen Dong
2022	A	`conf`	Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets. AISTATS Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong
2022	J	`jnl`	Graph similarity learning for change-point detection in dynamic networks. CoRR Déborah Sulem, Henry Kenlay, Mihai Cucuringu, Xiaowen Dong
2022	J	`jnl`	Learning Hypergraphs From Signals With Dual Smoothness Prior. CoRR Bohan Tang, Siheng Chen, Xiaowen Dong
2022	A*	`conf`	Learning to Infer Structures of Network Games. ICML Emanuele Rossi, Federico Monti, Yan Leng, Michael M. Bronstein, Xiaowen Dong
2022	J	`jnl`	Learning to Infer Structures of Network Games. CoRR Emanuele Rossi, Federico Monti, Yan Leng, Michael M. Bronstein, Xiaowen Dong
2022	J	`jnl`	Local2Global: A distributed approach for scaling representation learning on graphs. CoRR Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong, Marya Bazzi, Mihai Cucuringu
2022	J	`jnl`	Maximum Entropy Approach to Massive Graph Spectrum Learning with Applications. Algorithms Diego Granziol, Binxin Ru, Xiaowen Dong, Stefan Zohren, Michael A. Osborne, Stephen J. Roberts
2022	—	`conf`	Modeling Ideological Salience and Framing in Polarized Online Groups with Graph Neural Networks and Structured Sparsity. NAACL-HLT (Findings) Valentin Hofmann, Xiaowen Dong, Janet B. Pierrehumbert, Hinrich Schütze
2022	—	`conf`	On the Unreasonable Effectiveness of Feature Propagation in Learning on Graphs With Missing Node Features. LoG Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
2022	J	`jnl`	Transductive Kernels for Gaussian Processes on Graphs. CoRR Yin-Cong Zhi, Felix L. Opolka, Yin Cheng Ng, Pietro Liò, Xiaowen Dong
2022	A*	`conf`	Understanding over-squashing and bottlenecks on graphs via curvature. ICLR Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
2022	J	`jnl`	Understanding stock market instability via graph auto-encoders. CoRR Dragos Gorduza, Xiaowen Dong, Stefan Zohren
2022	J	`jnl`	Unrolled Graph Learning for Multi-Agent Collaboration. CoRR Enpei Zhang, Shuo Tang, Xiaowen Dong, Siheng Chen, Yanfeng Wang
2021	J	`jnl`	Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets. CoRR Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong
2021	J	`jnl`	Adversarial Attacks on Graph Classification via Bayesian Optimisation. CoRR Xingchen Wan, Henry Kenlay, Binxin Ru, Arno Blaas, Michael A. Osborne, Xiaowen Dong
2021	A*	`conf`	Adversarial Attacks on Graph Classifiers via Bayesian Optimisation. NeurIPS Xingchen Wan, Henry Kenlay, Robin Ru, Arno Blaas, Michael A. Osborne, Xiaowen Dong
2021	J	`jnl`	Bayesian Topology Learning and noise removal from network data. Discov. Internet Things Mahmoud Ramezani Mayiami, Mohammad Hajimirsadeghi, Karl Skretting, Xiaowen Dong, Rick S. Blum, H. Vincent Poor
2021	A*	`conf`	Beltrami Flow and Neural Diffusion on Graphs. NeurIPS Ben Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael M. Bronstein
2021	J	`jnl`	Beltrami Flow and Neural Diffusion on Graphs. CoRR Benjamin Paul Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael M. Bronstein
2021	J	`jnl`	Correction to: Bayesian Topology Learning and noise removal from network data. Discov. Internet Things Mahmoud Ramezani-Mayiami, Mohammad Hajimirsadeghi, Karl Skretting, Xiaowen Dong, Rick S. Blum, H. Vincent Poor
2021	A*	`conf`	Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels. ICLR Bin Xin Ru, Xingchen Wan, Xiaowen Dong, Michael A. Osborne
2021	A*	`conf`	Interpretable Stability Bounds for Spectral Graph Filters. ICML Henry Kenlay, Dorina Thanou, Xiaowen Dong
2021	J	`jnl`	Interpretable Stability Bounds for Spectral Graph Filters. CoRR Henry Kenlay, Dorina Thanou, Xiaowen Dong
2021	J	`jnl`	Kernel-Based Graph Learning From Smooth Signals: A Functional Viewpoint. IEEE Trans. Signal Inf. Process. over Networks Xingyue Pu, Siu Lun Chau, Xiaowen Dong, Dino Sejdinovic
2021	A*	`conf`	Learning to Learn Graph Topologies. NeurIPS Xingyue Pu, Tianyue Cao, Xiaoyun Zhang, Xiaowen Dong, Siheng Chen
2021	J	`jnl`	Learning to Learn Graph Topologies. CoRR Xingyue Pu, Tianyue Cao, Xiaoyun Zhang, Xiaowen Dong, Siheng Chen
2021	J	`jnl`	Local2Global: Scaling global representation learning on graphs via local training. CoRR Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong, Marya Bazzi, Mihai Cucuringu
2021	Misc	`conf`	On The Stability of Graph Convolutional Neural Networks Under Edge Rewiring. ICASSP Henry Kenlay, Dorina Thanou, Xiaowen Dong
2021	J	`jnl`	On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features. CoRR Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
2021	J	`jnl`	Understanding over-squashing and bottlenecks on graphs via curvature. CoRR Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein
2020	J	`jnl`	Gaussian Processes on Graphs via Spectral Kernel Learning. CoRR Yin-Cong Zhi, Yin Cheng Ng, Xiaowen Dong
2020	J	`jnl`	Graph Signal Processing for Machine Learning: A Review and New Perspectives. IEEE Signal Process. Mag. Xiaowen Dong, Dorina Thanou, Laura Toni, Michael M. Bronstein, Pascal Frossard
2020	J	`jnl`	Graph signal processing for machine learning: A review and new perspectives. CoRR Xiaowen Dong, Dorina Thanou, Laura Toni, Michael M. Bronstein, Pascal Frossard
2020	J	`jnl`	Kernel-based Graph Learning from Smooth Signals: A Functional Viewpoint. CoRR Xingyue Pu, Siu Lun Chau, Xiaowen Dong, Dino Sejdinovic
2020	A	`conf`	Laplacian-Regularized Graph Bandits: Algorithms and Theoretical Analysis. AISTATS Kaige Yang, Laura Toni, Xiaowen Dong
2020	A*	`conf`	Learning Quadratic Games on Networks. ICML Yan Leng, Xiaowen Dong, Junfeng Wu, Alex Pentland
2020	—	`conf`	Mobility Networks for Predicting Gentrification. COMPLEX NETWORKS (2) Oliver Gardiner, Xiaowen Dong
2020	J	`jnl`	Neural Architecture Search using Bayesian Optimisation with Weisfeiler-Lehman Kernel. CoRR Bin Xin Ru, Xingchen Wan, Xiaowen Dong, Michael A. Osborne
2020	Misc	`conf`	On The Stability of Polynomial Spectral Graph Filters. ICASSP Henry Kenlay, Dorina Thanou, Xiaowen Dong
2020	J	`jnl`	On the Stability of Graph Convolutional Neural Networks under Edge Rewiring. CoRR Henry Kenlay, Dorina Thanou, Xiaowen Dong
2020	J	`jnl`	Segregated interactions in urban and online space. EPJ Data Sci. Xiaowen Dong, Alfredo Jose Morales, Eaman Jahani, Esteban Moro, Bruno Lepri, Burçin Bozkaya, Carlos Sarraute, Yaneer Bar-Yam, Alex Pentland
2020	J	`jnl`	Sentiment Diffusion in Financial News Networks and Associated Market Movements. CoRR Xingchen Wan, Jie Yang, Slavi Marinov, Jan-Peter Calliess, Stefan Zohren, Xiaowen Dong
2019	J	`jnl`	A Maximum Entropy approach to Massive Graph Spectra. CoRR Diego Granziol, Robin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
2019	J	`jnl`	Error Analysis on Graph Laplacian Regularized Estimator. CoRR Kaige Yang, Xiaowen Dong, Laura Toni
2019	—	`ch.`	Introduction to the Data for Refugees Challenge on Mobility of Syrian Refugees in Turkey. Data for Refugees Challenge Albert Ali Salah, Alex Pentland, Bruno Lepri, Emmanuel Letouzé, Yves-Alexandre de Montjoye, Xiaowen Dong, Özge Dagdelen, Patrick Vinck
2019	J	`jnl`	Laplacian-regularized graph bandits: Algorithms and theoretical analysis. CoRR Kaige Yang, Xiaowen Dong, Laura Toni
2019	J	`jnl`	Learning Graphs From Data: A Signal Representation Perspective. IEEE Signal Process. Mag. Xiaowen Dong, Dorina Thanou, Michael G. Rabbat, Pascal Frossard
2019	J	`jnl`	MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. CoRR Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
2019	J	`jnl`	MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. Entropy Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
2019	J	`jnl`	Segregated interactions in urban and online spaces. CoRR Xiaowen Dong, Alfredo Jose Morales, Eaman Jahani, Esteban Moro, Bruno Lepri, Burçin Bozkaya, Carlos Sarraute, Yaneer Bar-Yam, Alex Pentland
2018	J	`jnl`	Behavioral attributes and financial churn prediction. EPJ Data Sci. Erdem Kaya, Xiaowen Dong, Yoshihiko Suhara, Selim Balcisoy, Burçin Bozkaya, Alex 'Sandy' Pentland
2018	J	`jnl`	Data for Refugees: The D4R Challenge on Mobility of Syrian Refugees in Turkey. CoRR Albert Ali Salah, Alex Pentland, Bruno Lepri, Emmanuel Letouzé, Patrick Vinck, Yves-Alexandre de Montjoye, Xiaowen Dong, Özge Dagdelen
2018	J	`jnl`	Entropic Spectral Learning in Large Scale Networks. CoRR Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts
2018	J	`jnl`	Learning Graphs from Data: A Signal Representation Perspective. CoRR Xiaowen Dong, Dorina Thanou, Michael G. Rabbat, Pascal Frossard
2018	J	`jnl`	Learning Quadratic Games on Networks. CoRR Yan Leng, Xiaowen Dong, Alex Pentland
2018	J	`jnl`	Methods for quantifying effects of social unrest using credit card transaction data. EPJ Data Sci. Xiaowen Dong, Joachim Meyer, Erez Shmueli, Burçin Bozkaya, Alex Pentland
2018	J	`jnl`	Social Bridges in Urban Purchase Behavior. ACM Trans. Intell. Syst. Technol. Xiaowen Dong, Yoshihiko Suhara, Burçin Bozkaya, Vivek K. Singh, Bruno Lepri, Alex 'Sandy' Pentland
2017	J	`jnl`	Learning Heat Diffusion Graphs. IEEE Trans. Signal Inf. Process. over Networks Dorina Thanou, Xiaowen Dong, Daniel Kressner, Pascal Frossard
2016	J	`jnl`	Learning Laplacian Matrix in Smooth Graph Signal Representations. IEEE Trans. Signal Process. Xiaowen Dong, Dorina Thanou, Pascal Frossard, Pierre Vandergheynst
2016	J	`jnl`	Learning heat diffusion graphs. CoRR Dorina Thanou, Xiaowen Dong, Daniel Kressner, Pascal Frossard
2016	C	`conf`	Multi-modal Image Retrieval with Random Walk on Multi-layer Graphs. ISM Renata Khasanova, Xiaowen Dong, Pascal Frossard
2016	J	`jnl`	Multi-modal image retrieval with random walk on multi-layer graphs. CoRR Renata Khasanova, Xiaowen Dong, Pascal Frossard
2015	Misc	`conf`	Laplacian matrix learning for smooth graph signal representation. ICASSP Xiaowen Dong, Dorina Thanou, Pascal Frossard, Pierre Vandergheynst
2015	J	`jnl`	Multiscale event detection in social media. Data Min. Knowl. Discov. Xiaowen Dong, Dimitrios Mavroeidis, Francesco Calabrese, Pascal Frossard
2014	J	`jnl`	Clustering on Multi-Layer Graphs via Subspace Analysis on Grassmann Manifolds. IEEE Trans. Signal Process. Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst, Nikolai Nefedov
2014	J	`jnl`	Learning Graphs from Signal Observations under Smoothness Prior. CoRR Xiaowen Dong, Dorina Thanou, Pascal Frossard, Pierre Vandergheynst
2014	J	`jnl`	Multiscale Event Detection in Social Media. CoRR Xiaowen Dong, Dimitrios Mavroeidis, Francesco Calabrese, Pascal Frossard
2013	J	`jnl`	Clustering on Multi-Layer Graphs via Subspace Analysis on Grassmann Manifolds CoRR Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst, Nikolai Nefedov
2013	—	`conf`	Clustering on multi-layer graphs via subspace analysis on Grassmann manifolds. GlobalSIP Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst, Nikolai Nefedov
2013	Misc	`conf`	Inference of mobility patterns via Spectral Graph Wavelets. ICASSP Xiaowen Dong, Antonio Ortega, Pascal Frossard, Pierre Vandergheynst
2013	—	`conf`	SaferCity: A System for Detecting and Analyzing Incidents from Social Media. ICDM Workshops Michele Berlingerio, Francesco Calabrese, Giusy Di Lorenzo, Xiaowen Dong, Yiannis Gkoufas, Dimitrios Mavroeidis
2012	J	`jnl`	Clustering With Multi-Layer Graphs: A Spectral Perspective. IEEE Trans. Signal Process. Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst, Nikolai Nefedov
2012	Misc	`conf`	Learning of structured graph dictionaries. ICASSP Xuan Zhang, Xiaowen Dong, Pascal Frossard
2012	J	`jnl`	Structural analysis of network traffic matrix via relaxed principal component pursuit. Comput. Networks Zhe Wang, Kai Hu, Ke Xu, Baolin Yin, Xiaowen Dong
2011	Misc	`conf`	A regularization framework for mobile social network analysis. ICASSP Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst, Nikolai Nefedov
2011	J	`jnl`	Clustering with Multi-Layer Graphs: A Spectral Perspective CoRR Xiaowen Dong, Pascal Frossard, Pierre Vandergheynst, Nikolai Nefedov