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2020 – today
- 2024
[c18]Hengrui Zhang
, Qitian Wu, Chenxiao Yang, Philip S. Yu:
InfoMLP: Unlocking the Potential of MLPs for Semi-Supervised Learning with Structured Data. CIKM 2024: 3155-3164- [c17]Qitian Wu, Fan Nie, Chenxiao Yang, Junchi Yan:
Learning Divergence Fields for Shift-Robust Graph Representations. ICML 2024 - [c16]Chenxiao Yang, Qitian Wu, David Wipf, Ruoyu Sun, Junchi Yan:
How Graph Neural Networks Learn: Lessons from Training Dynamics. ICML 2024 - [c15]Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan:
GeoMix: Towards Geometry-Aware Data Augmentation. KDD 2024: 4500-4511 - [c14]Qitian Wu, Fan Nie, Chenxiao Yang, Tianyi Bao, Junchi Yan:
Graph Out-of-Distribution Generalization via Causal Intervention. WWW 2024: 850-860 - [i15]Qitian Wu, Fan Nie, Chenxiao Yang, Tianyi Bao, Junchi Yan:
Graph Out-of-Distribution Generalization via Causal Intervention. CoRR abs/2402.11494 (2024) - [i14]Qitian Wu, Fan Nie, Chenxiao Yang, Junchi Yan:
Learning Divergence Fields for Shift-Robust Graph Representations. CoRR abs/2406.04963 (2024) - [i13]Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan:
GeoMix: Towards Geometry-Aware Data Augmentation. CoRR abs/2407.10681 (2024) - 2023
- [c13]Qitian Wu, Yiting Chen, Chenxiao Yang, Junchi Yan:
Energy-based Out-of-Distribution Detection for Graph Neural Networks. ICLR 2023 - [c12]Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf, Junchi Yan:
DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion. ICLR 2023 - [c11]Chenxiao Yang, Qitian Wu, Jiahua Wang, Junchi Yan:
Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs. ICLR 2023 - [c10]Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan:
GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks. KDD 2023: 3525-3536 - [c9]Qitian Wu, Wentao Zhao, Chenxiao Yang, Hengrui Zhang, Fan Nie, Haitian Jiang, Yatao Bian, Junchi Yan:
Simplifying and Empowering Transformers for Large-Graph Representations. NeurIPS 2023 - [i12]Qitian Wu, Chenxiao Yang, Wentao Zhao, Yixuan He, David Wipf, Junchi Yan:
DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion. CoRR abs/2301.09474 (2023) - [i11]Qitian Wu, Yiting Chen, Chenxiao Yang, Junchi Yan:
Energy-based Out-of-Distribution Detection for Graph Neural Networks. CoRR abs/2302.02914 (2023) - [i10]Qitian Wu, Wentao Zhao, Chenxiao Yang, Hengrui Zhang, Fan Nie, Haitian Jiang, Yatao Bian, Junchi Yan:
Simplifying and Empowering Transformers for Large-Graph Representations. CoRR abs/2306.10759 (2023) - [i9]Wentao Zhao, Qitian Wu, Chenxiao Yang, Junchi Yan:
GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks. CoRR abs/2306.11264 (2023) - [i8]Chenxiao Yang, Qitian Wu, David Wipf, Ruoyu Sun, Junchi Yan:
How Graph Neural Networks Learn: Lessons from Training Dynamics in Function Space. CoRR abs/2310.05105 (2023) - [i7]Qitian Wu, Chenxiao Yang, Kaipeng Zeng, Fan Nie, Michael M. Bronstein, Junchi Yan:
Advective Diffusion Transformers for Topological Generalization in Graph Learning. CoRR abs/2310.06417 (2023) - 2022
- [j1]Yuwen Sha, Sun Bo, Chenxiao Yang, Jun Mou, Hadi Jahanshahi:
A Chaotic Image Encryption Scheme Based on Genetic Central Dogma and KMP Method. Int. J. Bifurc. Chaos 32(12): 2250186:1-2250186:23 (2022) - [c8]Chenxiao Yang, Junwei Pan, Xiaofeng Gao, Tingyu Jiang, Dapeng Liu, Guihai Chen:
Cross-Task Knowledge Distillation in Multi-Task Recommendation. AAAI 2022: 4318-4326 - [c7]Chenxiao Yang, Qitian Wu, Jipeng Jin, Xiaofeng Gao, Junwei Pan, Guihai Chen:
Trading Hard Negatives and True Negatives: A Debiased Contrastive Collaborative Filtering Approach. IJCAI 2022: 2355-2361 - [c6]Chenxiao Yang, Qitian Wu, Qingsong Wen, Zhiqiang Zhou, Liang Sun, Junchi Yan:
Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment. NeurIPS 2022 - [c5]Chenxiao Yang, Qitian Wu, Junchi Yan:
Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks. NeurIPS 2022 - [i6]Chenxiao Yang, Junwei Pan, Xiaofeng Gao, Tingyu Jiang, Dapeng Liu, Guihai Chen:
Cross-Task Knowledge Distillation in Multi-Task Recommendation. CoRR abs/2202.09852 (2022) - [i5]Chenxiao Yang, Qitian Wu, Jipeng Jin, Xiaofeng Gao, Junwei Pan, Guihai Chen:
Trading Hard Negatives and True Negatives: A Debiased Contrastive Collaborative Filtering Approach. CoRR abs/2204.11752 (2022) - [i4]Chenxiao Yang, Qitian Wu, Qingsong Wen, Zhiqiang Zhou, Liang Sun, Junchi Yan:
Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment. CoRR abs/2210.13005 (2022) - [i3]Chenxiao Yang, Qitian Wu, Junchi Yan:
Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks. CoRR abs/2210.13014 (2022) - [i2]Chenxiao Yang, Qitian Wu, Jiahua Wang, Junchi Yan:
Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs. CoRR abs/2212.09034 (2022) - 2021
- [c4]Qitian Wu, Chenxiao Yang, Shuodian Yu, Xiaofeng Gao, Guihai Chen:
Seq2Bubbles: Region-Based Embedding Learning for User Behaviors in Sequential Recommenders. CIKM 2021: 2160-2169 - [c3]Chenxiao Yang, Jiale Zhang, Xiaofeng Gao, Guihai Chen:
MatTrip: Multi-functional Attention-based Neural Network for Semantic Travel Route Recommendation. ICWS 2021: 145-154 - [c2]Qitian Wu, Chenxiao Yang, Junchi Yan:
Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach. NeurIPS 2021: 19435-19447 - [i1]Qitian Wu, Chenxiao Yang, Junchi Yan:
Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach. CoRR abs/2110.04514 (2021)
2000 – 2009
- 2006
- [c1]Chenxiao Yang, Xizhao Wang, Ruixian Zhu:
A Strategy of Merging Branches Based on Margin Enlargement of SVM in Decision Tree Induction. SMC 2006: 824-828
Coauthor Index
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