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Self-supervised Amodal Video Object Segmentation


Oct 23, 2022
Jian Yao, Yuxin Hong, Chiyu Wang, Tianjun Xiao, Tong He, Francesco Locatello, David Wipf, Yanwei Fu, Zheng Zhang

* accepted in Neurips2022 

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Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks


Jun 24, 2022
Hongjoon Ahn, Yongyi Yang, Quan Gan, David Wipf, Taesup Moon


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A Robust Stacking Framework for Training Deep Graph Models with Multifaceted Node Features


Jun 16, 2022
Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Tom Goldstein, David Wipf


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Learning Enhanced Representations for Tabular Data via Neighborhood Propagation


Jun 14, 2022
Kounianhua Du, Weinan Zhang, Ruiwen Zhou, Yangkun Wang, Xilong Zhao, Jiarui Jin, Quan Gan, Zheng Zhang, David Wipf


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Transformers from an Optimization Perspective


May 27, 2022
Yongyi Yang, Zengfeng Huang, David Wipf


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Handling Distribution Shifts on Graphs: An Invariance Perspective


Feb 05, 2022
Qitian Wu, Hengrui Zhang, Junchi Yan, David Wipf

* ICLR2022, 31 pages 

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GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks


Feb 01, 2022
Yixuan He, Quan Gan, David Wipf, Gesine Reinert, Junchi Yan, Mihai Cucuringu

* 33 pages (8 pages for main text) 

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Implicit vs Unfolded Graph Neural Networks


Nov 12, 2021
Yongyi Yang, Yangkun Wang, Zengfeng Huang, David Wipf


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Convergent Boosted Smoothing for Modeling Graph Data with Tabular Node Features


Oct 26, 2021
Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf


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