no code implementations • 14 Nov 2023 • Yangfan Li, Satyajit Mojumder, Ye Lu, Abdullah Al Amin, Jiachen Guo, Xiaoyu Xie, Wei Chen, Gregory J. Wagner, Jian Cao, Wing Kam Liu
In the context of laser powder bed fusion (LPBF) additive manufacturing, a digital twin of the manufacturing process can offer predictions for the produced parts, diagnostics for manufacturing defects, as well as control capabilities.
no code implementations • 7 Apr 2023 • Cheng Gong, Ye Lu, Surong Dai, Deng Qian, Chenkun Du, Tao Li
QSS introduces five quantizing schemes and defines three new schemes as a candidate set for scheme search, and then uses the differentiable neural architecture search (DNAS) algorithm to seek the layer- or model-desired scheme from the set.
no code implementations • 9 Oct 2021 • Keyu Li, Ye Lu, Max Q. -H. Meng
In recent years, the growing demand for more intelligent service robots is pushing the development of mobile robot navigation algorithms to allow safe and efficient operation in a dense crowd.
no code implementations • 8 Sep 2021 • Cheng Gong, Ye Lu, Kunpeng Xie, Zongming Jin, Tao Li, Yanzhi Wang
We implement ESB as an accelerator and quantitatively evaluate its efficiency on FPGAs.
no code implementations • 13 May 2021 • Lei Zhang, Ye Lu, Shaoqiang Tang, Wing Kam Liu
This paper presents a proper generalized decomposition (PGD) based reduced-order model of hierarchical deep-learning neural networks (HiDeNN).
no code implementations • 7 Apr 2021 • Giuseppe Cavaliere, Ye Lu, Anders Rahbek, Jacob Stærk-Østergaard
Inference and testing in general point process models such as the Hawkes model is predominantly based on asymptotic approximations for likelihood-based estimators and tests.
no code implementations • 16 Mar 2021 • Qihang Yang, Tao Chen, Jiayuan Fan, Ye Lu, Chongyan Zuo, Qinghua Chi
Due to real-time image semantic segmentation needs on power constrained edge devices, there has been an increasing desire to design lightweight semantic segmentation neural network, to simultaneously reduce computational cost and increase inference speed.
no code implementations • CUHK Course IERG5350 2020 • Keyu Li, Ye Lu
In recent years, the growing demand for more intelligent service robots is pushing the development of mobile robot navigation algorithms.
1 code implementation • 18 May 2020 • Cheng Gong, Yao Chen, Ye Lu, Tao Li, Cong Hao, Deming Chen
Quantization has been proven to be an effective method for reducing the computing and/or storage cost of DNNs.