Dong, Xiaowen

36 publications

ICLR 2025 Bundle Neural Network for Message Diffusion on Graphs Jacob Bamberger, Federico Barbero, Xiaowen Dong, Michael M. Bronstein

AISTATS 2025 Heterogeneous Graph Structure Learning Through the Lens of Data-Generating Processes Keyue Jiang, Bohan Tang, Xiaowen Dong, Laura Toni

ICLR 2025 Neural Spacetimes for DAG Representation Learning Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T. Law, Xiaowen Dong, Michael M. Bronstein

ICML 2025 On Measuring Long-Range Interactions in Graph Neural Networks Jacob Bamberger, Benjamin Gutteridge, Scott Le Roux, Michael M. Bronstein, Xiaowen Dong

NeurIPS 2025 On Vanishing Gradients, Over-Smoothing, and Over-Squashing in GNNs: Bridging Recurrent and Graph Learning Alvaro Arroyo, Alessio Gravina, Benjamin Gutteridge, Federico Barbero, Claudio Gallicchio, Xiaowen Dong, Michael M. Bronstein, Pierre Vandergheynst

NeurIPS 2025 On the Stability of Graph Convolutional Neural Networks: A Probabilistic Perspective Ning Zhang, Henry Kenlay, Li Zhang, Mihai Cucuringu, Xiaowen Dong

NeurIPS 2025 Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks Ali Hariri, Alvaro Arroyo, Alessio Gravina, Moshe Eliasof, Carola-Bibiane Schönlieb, Davide Bacciu, Xiaowen Dong, Kamyar Azizzadenesheli, Pierre Vandergheynst

ICLR 2025 Separation Power of Equivariant Neural Networks Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin

ICLR 2025 Training-Free Message Passing for Learning on Hypergraphs Bohan Tang, Zexi Liu, Keyue Jiang, Siheng Chen, Xiaowen Dong

ICLR 2024 A Characterization Theorem for Equivariant Networks with Point-Wise Activations Marco Pacini, Xiaowen Dong, Bruno Lepri, Gabriele Santin

NeurIPS 2024 Bayesian Optimization of Functions over Node Subsets in Graphs Huidong Liang, Xingchen Wan, Xiaowen Dong

ICMLW 2024 Bundle Neural Networks for Message Diffusion on Graphs Jacob Bamberger, Federico Barbero, Xiaowen Dong, Michael M. Bronstein

NeurIPSW 2024 Graph Classification Gaussian Processes via Hodgelet Spectral Features Mathieu Alain, So Takao, Bastian Rieck, Xiaowen Dong, Emmanuel Noutahi

MLJ 2024 Graph Similarity Learning for Change-Point Detection in Dynamic Networks Déborah Sulem, Henry Kenlay, Mihai Cucuringu, Xiaowen Dong

NeurIPS 2024 Rough Transformers: Lightweight and Continuous Time Series Modelling Through Signature Patching Fernando Moreno-Pino, Álvaro Arroyo, Harrison Waldon, Xiaowen Dong, Álvaro Cartea

NeurIPS 2023 Bayesian Optimisation of Functions on Graphs Xingchen Wan, Pierre Osselin, Henry Kenlay, Binxin Ru, Michael A Osborne, Xiaowen Dong

ICML 2023 DRew: Dynamically Rewired Message Passing with Delay Benjamin Gutteridge, Xiaowen Dong, Michael M. Bronstein, Francesco Di Giovanni

UAI 2023 Graph Classification Gaussian Processes via Spectral Features Felix L. Opolka, Yin-Cong Zhi, Pietro Liò, Xiaowen Dong

ICMLW 2023 Gromov-Hausdorff Distances for Comparing Product Manifolds of Model Spaces Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ismael Morales, Ingmar Posner, Xiaowen Dong

MLJ 2023 Local2Global: A Distributed Approach for Scaling Representation Learning on Graphs Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong, Marya Bazzi, Mihai Cucuringu

NeurIPS 2023 Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ismael Morales, Ingmar Posner, Xiaowen Dong

UAI 2023 Structure-Aware Robustness Certificates for Graph Classification Pierre Osselin, Henry Kenlay, Xiaowen Dong

AISTATS 2022 Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets Felix Opolka, Yin-Cong Zhi, Pietro Lió, Xiaowen Dong

ICML 2022 Learning to Infer Structures of Network Games Emanuele Rossi, Federico Monti, Yan Leng, Michael Bronstein, Xiaowen Dong

LoG 2022 On the Unreasonable Effectiveness of Feature Propagation in Learning on Graphs with Missing Node Features Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein

NeurIPSW 2022 On the Unreasonable Effectiveness of Feature Propagation in Learning on Graphs with Missing Node Features Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein

ICLR 2022 Understanding Over-Squashing and Bottlenecks on Graphs via Curvature Jake Topping, Francesco Di Giovanni, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein

NeurIPS 2021 Adversarial Attacks on Graph Classifiers via Bayesian Optimisation Xingchen Wan, Henry Kenlay, Robin Ru, Arno Blaas, Michael A Osborne, Xiaowen Dong

ICMLW 2021 Attacking Graph Classification via Bayesian Optimisation Xingchen Wan, Henry Kenlay, Binxin Ru, Arno Blaas, Michael Osborne, Xiaowen Dong

NeurIPS 2021 Beltrami Flow and Neural Diffusion on Graphs Benjamin Chamberlain, James Rowbottom, Davide Eynard, Francesco Di Giovanni, Xiaowen Dong, Michael Bronstein

ICLR 2021 Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels Binxin Ru, Xingchen Wan, Xiaowen Dong, Michael Osborne

ICML 2021 Interpretable Stability Bounds for Spectral Graph Filters Henry Kenlay, Dorina Thanou, Xiaowen Dong

NeurIPS 2021 Learning to Learn Graph Topologies Xingyue Pu, Tianyue Cao, Xiaoyun Zhang, Xiaowen Dong, Siheng Chen

ICLRW 2021 On the Stability of Graph Convolutional Neural Networks Under Edge Rewiring Henry Kenlay, Dorina Thanou, Xiaowen Dong

AISTATS 2020 Laplacian-Regularized Graph Bandits: Algorithms and Theoretical Analysis Kaige Yang, Laura Toni, Xiaowen Dong

ICML 2020 Learning Quadratic Games on Networks Yan Leng, Xiaowen Dong, Junfeng Wu, Alex Pentland