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


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

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* Accepted by International Conference on Learning Representations (ICLR 2023) 

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HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline


Feb 04, 2023
Yang Li, Xinyan Chen, Wenxuan Guo, Xijun Li, Wanqian Luo, Junhua Huang, Hui-Ling Zhen, Mingxuan Yuan, Junchi Yan

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


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

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* Accepted by International Conference on Learning Representations (ICLR 2023) 

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Policy Pre-training for End-to-end Autonomous Driving via Self-supervised Geometric Modeling


Jan 03, 2023
Penghao Wu, Li Chen, Hongyang Li, Xiaosong Jia, Junchi Yan, Yu Qiao

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* 16 pages, 7 figures 

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


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

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Localized Contrastive Learning on Graphs


Dec 08, 2022
Hengrui Zhang, Qitian Wu, Yu Wang, Shaofeng Zhang, Junchi Yan, Philip S. Yu

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Leveraging Angular Information Between Feature and Classifier for Long-tailed Learning: A Prediction Reformulation Approach


Dec 03, 2022
Haoxuan Wang, Junchi Yan

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Geometric Knowledge Distillation: Topology Compression for Graph Neural Networks


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

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* in NeurIPS 2022 

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


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

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* in NeurIPS 2022 

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Learning Universe Model for Partial Matching Networks over Multiple Graphs


Oct 19, 2022
Zetian Jiang, Jiaxin Lu, Tianzhe Wang, Junchi Yan

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* 17 pages, 16 figures 

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