no code implementations • 24 Nov 2023 • Taofeng Xie, Zhuo-Xu Cui, Chen Luo, Huayu Wang, Congcong Liu, Yuanzhi Zhang, Xuemei Wang, Yanjie Zhu, Qiyu Jin, Guoqing Chen, Yihang Zhou, Dong Liang, Haifeng Wang
The complementary information can contribute to image reconstruction.
no code implementations • 7 Oct 2023 • Yuanyuan Liu, Zhuo-Xu Cui, Congcong Liu, Hairong Zheng, Haifeng Wang, Yihang Zhou, Yanjie Zhu
Long scan time significantly hinders the widespread applications of three-dimensional multi-contrast cardiac magnetic resonance (3D-MC-CMR) imaging.
no code implementations • 30 Aug 2023 • Zhuo-Xu Cui, Congcong Liu, Xiaohong Fan, Chentao Cao, Jing Cheng, Qingyong Zhu, Yuanyuan Liu, Sen Jia, Yihang Zhou, Haifeng Wang, Yanjie Zhu, Jianping Zhang, Qiegen Liu, Dong Liang
In order to enhance interpretability and overcome the acceleration limitations, this paper introduces an interpretable framework that unifies both $k$-space interpolation techniques and image-domain methods, grounded in the physical principles of heat diffusion equations.
no code implementations • 5 Aug 2023 • Fanshi Li, Zhihui Wang, Yifan Guo, Congcong Liu, Yanjie Zhu, Yihang Zhou, Jun Li, Dong Liang, Haifeng Wang
In this paper, a dynamic dual-graph fusion convolutional network is proposed to improve Alzheimer's disease (AD) diagnosis performance.
no code implementations • 28 Jun 2023 • Jian Zhu, Congcong Liu, Pei Wang, Xiwei Zhao, Zhangang Lin, Jingping Shao
Model evolution and constant availability of data are two common phenomena in large-scale real-world machine learning applications, e. g. ads and recommendation systems.
no code implementations • 4 May 2023 • Zhuo-Xu Cui, Congcong Liu, Chentao Cao, Yuanyuan Liu, Jing Cheng, Qingyong Zhu, Yanjie Zhu, Haifeng Wang, Dong Liang
We theoretically uncovered that the combination of these challenges renders conventional deep learning methods that directly learn the mapping from a low-field MR image to a high-field MR image unsuitable.
no code implementations • 17 Apr 2023 • Congcong Liu, Fei Teng, Xiwei Zhao, Zhangang Lin, Jinghe Hu, Jingping Shao
Streaming data has the characteristic that the underlying distribution drifts over time and may recur.
1 code implementation • 11 Aug 2022 • Zhuo-Xu Cui, Sen Jia, Qingyong Zhu, Congcong Liu, Zhilang Qiu, Yuanyuan Liu, Jing Cheng, Haifeng Wang, Yanjie Zhu, Dong Liang
Recently, untrained neural networks (UNNs) have shown satisfactory performances for MR image reconstruction on random sampling trajectories without using additional full-sampled training data.
no code implementations • 26 Jun 2022 • Han Xu, Hao Qi, Kunyao Wang, Pei Wang, Guowei Zhang, Congcong Liu, Junsheng Jin, Xiwei Zhao, Zhangang Lin, Jinghe Hu, Jingping Shao
In this work, we propose a novel framework PCDF(Parallel-Computing Distributed Framework), allowing to split the computation cost into three parts and to deploy them in the pre-module in parallel with the retrieval stage, the middle-module for ranking ads, and the post-module for re-ranking ads with external items.
no code implementations • 9 May 2022 • Chentao Cao, Zhuo-Xu Cui, Qingyong Zhu, Congcong Liu, Dong Liang, Yanjie Zhu
In this paper, we propose a learned low-rank method for dynamic MR imaging.
1 code implementation • 8 Apr 2022 • Yinan Zhang, Pei Wang, Congcong Liu, Xiwei Zhao, Hao Qi, Jie He, Junsheng Jin, Changping Peng, Zhangang Lin, Jingping Shao
In this work, we address this problem by building bilateral interactive guidance between each user-item pair and proposing a new model named IA-GCN (short for InterActive GCN).
no code implementations • 1 Apr 2022 • Congcong Liu, Yuejiang Li, Jian Zhu, Xiwei Zhao, Changping Peng, Zhangang Lin, Jingping Shao
Click-through rate (CTR) Prediction is of great importance in real-world online ads systems.
no code implementations • 1 Apr 2022 • Congcong Liu, Yuejiang Li, Fei Teng, Xiwei Zhao, Changping Peng, Zhangang Lin, Jinghe Hu, Jingping Shao
Click-through rate (CTR) prediction is a crucial task in web search, recommender systems, and online advertisement displaying.
no code implementations • 9 Nov 2021 • Jian Zhu, Congcong Liu, Pei Wang, Xiwei Zhao, Guangpeng Chen, Junsheng Jin, Changping Peng, Zhangang Lin, Jingping Shao
Learning to capture feature relations effectively and efficiently is essential in click-through rate (CTR) prediction of modern recommendation systems.
no code implementations • 1 Feb 2021 • Xiaodong Mei, Yuxiang Sun, Yuying Chen, Congcong Liu, Ming Liu
To provide a solution to this problem, we propose a novel branched network G-CIL for the navigation policy learning.
no code implementations • 14 Jan 2021 • Congcong Liu, Yuying Chen, Ming Liu, Bertram E. Shi
We suggest that introducing an attention mechanism to infer the importance of different neighbors is critical for accurate trajectory prediction in scenes with varying crowd size.
no code implementations • 15 Sep 2020 • Yuying Chen, Congcong Liu, Xiaodong Mei, Bertram E. Shi, Ming Liu
Fully investigating the social interactions within the crowd is crucial for accurate pedestrian trajectory prediction.
no code implementations • 2 May 2020 • Yuying Chen, Congcong Liu, Bertram Shi, Ming Liu
Forecasting human trajectories is critical for tasks such as robot crowd navigation and autonomous driving.
no code implementations • 23 Sep 2019 • Yuying Chen, Congcong Liu, Ming Liu, Bertram E. Shi
Previous work has shown the power of deep reinforcement learning frameworks to train efficient policies.
no code implementations • 22 Jul 2019 • Guangcun Shan, Hongyu Wang, Wei Liang, Congcong Liu, Qizi Ma, Quan Quan
Recently, deep learning technology have been extensively used in the field of image recognition.
no code implementations • 10 Jul 2019 • Congcong Liu, Yuying Chen, Lei Tai, Ming Liu, Bertram Shi
Vision-based autonomous driving through imitation learning mimics the behaviors of human drivers by training on pairs of data of raw driver-view images and actions.
no code implementations • 17 Apr 2019 • Yuying Chen, Congcong Liu, Lei Tai, Ming Liu, Bertram E. Shi
The basic idea behind behavioral cloning is to have the neural network learn from observing a human expert's behavior.
1 code implementation • 3 Mar 2019 • Lei Tai, Peng Yun, Yuying Chen, Congcong Liu, Haoyang Ye, Ming Liu
End-to-end visual-based imitation learning has been widely applied in autonomous driving.