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2020 – today
- 2024
[c11]Xueyuan Liu, Zhuoran Song, Hao Chen, Xing Li, Xiaoyao Liang:
MoC: A Morton-Code-Based Fine-Grained Quantization for Accelerating Point Cloud Neural Networks. DAC 2024: 42:1-42:6- [c10]Xueyuan Liu, Zhuoran Song, Guohao Dai, Gang Li, Can Xiao, Yan Xiang, Dehui Kong, Ke Xu, Xiaoyao Liang:
FusionArch: A Fusion-Based Accelerator for Point-Based Point Cloud Neural Networks. DATE 2024: 1-6 - [c9]Xueyuan Liu, Zhuoran Song, Xiang Liao, Xing Li, Tao Yang, Fangxin Liu, Xiaoyao Liang:
Sava: A Spatial- and Value-Aware Accelerator for Point Cloud Transformer. DATE 2024: 1-6 - 2023
- [j6]Zongkai Zhu
, Chao He, Jiaqiang Li, Xueyuan Liu, Rong Ma:
The Prediction Model for Road Slope of Electric Vehicles Based on Stacking Framework of Deep Learning. IEEE Access 11: 22880-22888 (2023) - [c8]Chuliang Guo, Binglei Lou, Xueyuan Liu, David Boland, Philip H. W. Leong:
Single-Batch CNN Training using Block Minifloats on FPGAs. FPGA 2023: 53 - [c7]Chuliang Guo, Binglei Lou, Xueyuan Liu, David Boland, Philip H. W. Leong, Cheng Zhuo:
BOOST: Block Minifloat-Based On-Device CNN Training Accelerator with Transfer Learning. ICCAD 2023: 1-9 - 2022
- [j5]Xueyuan Liu, Carol Jingyi Li, Craig T. Jin, Philip H. W. Leong:
Wireless Signal Representation Techniques for Automatic Modulation Classification. IEEE Access 10: 84166-84187 (2022) - [c6]Xing Li, Rachata Ausavarungnirun, Xiao Liu, Xueyuan Liu, Xuan Zhang, Heng Lu, Zhuoran Song, Naifeng Jing, Xiaoyao Liang:
Gzippo: Highly-Compact Processing-in-Memory Graph Accelerator Alleviating Sparsity and Redundancy. ICCAD 2022: 115:1-115:9 - 2021
- [c5]Kaimo Ni, Xueyuan Liu:
A Matlab-Based Model of Diesel Engine Particulate Matter Lung Deposition. ACAI 2021: 20:1-20:5 - [c4]Wei Wei, Lin Xu, Chang Liu, Caiyuan Zhang, Lei Ai, Dan Jin, Xueyuan Liu, Hua Yang:
A Harmonic Model of EMU Based on Measured Data for Power Quality Pre-assessment. ICAIIS 2021: 72:1-72:7 - [c3]Xueyuan Liu:
Automatic Modulation Classification Based on Improved R-Transformer. IWCMC 2021: 1-8 - 2020
- [j4]Julian Faraone, Martin Kumm, Martin Hardieck, Peter Zipf, Xueyuan Liu, David Boland, Philip H. W. Leong:
AddNet: Deep Neural Networks Using FPGA-Optimized Multipliers. IEEE Trans. Very Large Scale Integr. Syst. 28(1): 115-128 (2020) - [c2]Zhuoran Song, Feiyang Wu, Xueyuan Liu, Jing Ke, Naifeng Jing, Xiaoyao Liang:
VR-DANN: Real-Time Video Recognition via Decoder-Assisted Neural Network Acceleration. MICRO 2020: 698-710
2010 – 2019
- 2019
- [j3]Guilin Meng, Yong Huang, Qi Yu, Ying Ding, David J. Wild, Yanxin Zhao, Xueyuan Liu, Min Song:
Adopting Text Mining on Rehabilitation Therapy Repositioning for Stroke. Frontiers Neuroinformatics 13: 17 (2019) - [i1]Julian Faraone, Martin Kumm, Martin Hardieck, Peter Zipf, Xueyuan Liu, David Boland, Philip H. W. Leong:
AddNet: Deep Neural Networks Using FPGA-Optimized Multipliers. CoRR abs/1911.08097 (2019) - 2018
- [j2]Guilin Meng, Xiulin Meng, Xiaoye Ma, Gengping Zhang, Xiaolin Hu, Aiping Jin, Yanxin Zhao, Xueyuan Liu:
Application of Ferulic Acid for Alzheimer's Disease: Combination of Text Mining and Experimental Validation. Frontiers Neuroinformatics 12: 31 (2018) - [j1]Xueyuan Liu, Haiyun Zhao, Xiande Zhao:
Absorptive capacity and business performance: The mediating effects of innovation and mass customization. Ind. Manag. Data Syst. 118(9): 1787-1803 (2018)
2000 – 2009
- 2008
- [c1]Jiang Li, Yongjuan Li, Xueyuan Liu:
The effects of motor impulsiveness and optimism bias on risky driving behavior in Chinese urban areas. ITSC 2008: 605-609
Coauthor Index
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