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Wei Deng

Bayesian Sparse learning with preconditioned stochastic gradient MCMC and its applications

Jun 29, 2020
Yating Wang, Wei Deng, Lin Guang

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NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results

May 05, 2020
Andreas Lugmayr, Martin Danelljan, Radu Timofte, Namhyuk Ahn, Dongwoon Bai, Jie Cai, Yun Cao, Junyang Chen, Kaihua Cheng, SeYoung Chun, Wei Deng, Mostafa El-Khamy, Chiu Man Ho, Xiaozhong Ji, Amin Kheradmand, Gwantae Kim, Hanseok Ko, Kanghyu Lee, Jungwon Lee, Hao Li, Ziluan Liu, Zhi-Song Liu, Shuai Liu, Yunhua Lu, Zibo Meng, Pablo Navarrete Michelini, Christian Micheloni, Kalpesh Prajapati, Haoyu Ren, Yong Hyeok Seo, Wan-Chi Siu, Kyung-Ah Sohn, Ying Tai, Rao Muhammad Umer, Shuangquan Wang, Huibing Wang, Timothy Haoning Wu, Haoning Wu, Biao Yang, Fuzhi Yang, Jaejun Yoo, Tongtong Zhao, Yuanbo Zhou, Haijie Zhuo, Ziyao Zong, Xueyi Zou

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An Adaptive Empirical Bayesian Method for Sparse Deep Learning

Oct 23, 2019
Wei Deng, Xiao Zhang, Faming Liang, Guang Lin

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* Accepted by NeurIPS 2019

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Using Deep Neural Networks to Automate Large Scale Statistical Analysis for Big Data Applications

Aug 09, 2017
Rongrong Zhang, Wei Deng, Michael Yu Zhu

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Adaptive low rank and sparse decomposition of video using compressive sensing

May 31, 2013
Fei Yang, Hong Jiang, Zuowei Shen, Wei Deng, Dimitris Metaxas

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* IEEE International Conference on Image Processing, ICIP 2013, Paper #1870
* Accepted ICIP 2013

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Surveillance Video Processing Using Compressive Sensing

Feb 08, 2013
Hong Jiang, Wei Deng, Zuowei Shen

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* Inverse Problems and Imaging, Volume 6, No. 2, 2012, 201-214
* 14 pages, 5 figures

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