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A Survey on Uncertainty Reasoning and Quantification for Decision Making: Belief Theory Meets Deep Learning


Jun 14, 2022
Zhen Guo, Zelin Wan, Qisheng Zhang, Xujiang Zhao, Feng Chen, Jin-Hee Cho, Qi Zhang, Lance M. Kaplan, Dong H. Jeong, Audun Jøsang

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* First four authors contributed equally 

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Layer Adaptive Deep Neural Networks for Out-of-distribution Detection


Mar 01, 2022
Haoliang Wang, Chen Zhao, Xujiang Zhao, Feng Chen

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* accepted in PAKDD 2022 

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SEED: Sound Event Early Detection via Evidential Uncertainty


Feb 13, 2022
Xujiang Zhao, Xuchao Zhang, Wei Cheng, Wenchao Yu, Yuncong Chen, Haifeng Chen, Feng Chen

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* ICASSP 2022 

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Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty Estimation


Sep 01, 2021
Liyan Xu, Xuchao Zhang, Xujiang Zhao, Haifeng Chen, Feng Chen, Jinho D. Choi

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* Accepted to EMNLP 2021 

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RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning


Jun 14, 2021
Krishnateja Killamsetty, Xujiang Zhao, Feng Chen, Rishabh Iyer

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Multidimensional Uncertainty-Aware Evidential Neural Networks


Dec 26, 2020
Yibo Hu, Yuzhe Ou, Xujiang Zhao, Jin-Hee Cho, Feng Chen

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* AAAI 2021 

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Uncertainty Aware Semi-Supervised Learning on Graph Data


Oct 24, 2020
Xujiang Zhao, Feng Chen, Shu Hu, Jin-Hee Cho

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* 27 pages 

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Robust Semi-Supervised Learning with Out of Distribution Data


Oct 07, 2020
Xujiang Zhao, Killamsetty Krishnateja, Rishabh Iyer, Feng Chen

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* Preprint 

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Quantifying Classification Uncertainty using Regularized Evidential Neural Networks


Oct 15, 2019
Xujiang Zhao, Yuzhe Ou, Lance Kaplan, Feng Chen, Jin-Hee Cho

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* Presented at AAAI FSS-19: Artificial Intelligence in Government and Public Sector, Arlington, Virginia, USA 

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