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Chenxiao Yang

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Graph Out-of-Distribution Generalization via Causal Intervention

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Feb 18, 2024
Qitian Wu, Fan Nie, Chenxiao Yang, Tianyi Bao, Junchi Yan

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Advective Diffusion Transformers for Topological Generalization in Graph Learning

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Oct 10, 2023
Qitian Wu, Chenxiao Yang, Kaipeng Zeng, Fan Nie, Michael Bronstein, Junchi Yan

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How Graph Neural Networks Learn: Lessons from Training Dynamics in Function Space

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Oct 08, 2023
Chenxiao Yang, Qitian Wu, David Wipf, Ruoyu Sun, Junchi Yan

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GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks

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Jun 20, 2023
Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan

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Simplifying and Empowering Transformers for Large-Graph Representations

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Jun 19, 2023
Qitian Wu, Wentao Zhao, Chenxiao Yang, Hengrui Zhang, Fan Nie, Haitian Jiang, Yatao Bian, Junchi Yan

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Energy-based Out-of-Distribution Detection for Graph Neural Networks

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Feb 06, 2023
Qitian Wu, Yiting Chen, Chenxiao Yang, Junchi Yan

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DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion

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Jan 23, 2023
Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf, Junchi Yan

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Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs

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Dec 18, 2022
Chenxiao Yang, Qitian Wu, Jiahua Wang, Junchi Yan

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Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment

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Oct 24, 2022
Chenxiao Yang, Qitian Wu, Qingsong Wen, Zhiqiang Zhou, Liang Sun, Junchi Yan

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Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks

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Oct 24, 2022
Chenxiao Yang, Qitian Wu, Junchi Yan

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