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Xiangnan Kong

ERNet: Unsupervised Collective Extraction and Registration in Neuroimaging Data

Dec 06, 2022
Yao Su, Zhentian Qian, Lifang He, Xiangnan Kong

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* Published as a research track paper at KDD 2022. Code: https://github.com/ERNetERNet/ERNet

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ABN: Anti-Blur Neural Networks for Multi-Stage Deformable Image Registration

Dec 06, 2022
Yao Su, Xin Dai, Lifang He, Xiangnan Kong

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* Published as a full paper at ICDM 2022. Code: https://github.com/anonymous3214/ABN

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Stop&Hop: Early Classification of Irregular Time Series

Aug 21, 2022
Thomas Hartvigsen, Walter Gerych, Jidapa Thadajarassiri, Xiangnan Kong, Elke Rundensteiner

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* This paper was accepted to CIKM'22. Code at https://github.com/thartvigsen/StopAndHop

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Self-learn to Explain Siamese Networks Robustly

Sep 15, 2021
Chao Chen, Yifan Shen, Guixiang Ma, Xiangnan Kong, Srinivas Rangarajan, Xi Zhang, Sihong Xie

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* Accepted to ICDM 2021

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MLAS: Metric Learning on Attributed Sequences

Nov 08, 2020
Zhongfang Zhuang, Xiangnan Kong, Elke Rundensteiner, Jihane Zouaoui, Aditya Arora

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* Accepted by IEEE Big Data 2020

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Attributed Sequence Embedding

Nov 03, 2019
Zhongfang Zhuang, Xiangnan Kong, Elke Rundensteiner, Jihane Zouaoui, Aditya Arora

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* Accepted by IEEE Big Data 2019

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Signed Distance-based Deep Memory Recommender

May 01, 2019
Thanh Tran, Xinyue Liu, Kyumin Lee, Xiangnan Kong

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* Proceedings of the 2019 World Wide Web Conference

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