no code implementations • 4 Dec 2023 • Wei Chen, Huaiyu Wan, Yuting Wu, Shuyuan Zhao, Jiayaqi Cheng, Yuxin Li, Youfang Lin
Temporal knowledge graphs (TKGs) have been identified as a promising approach to represent the dynamics of facts along the timeline.
1 code implementation • 20 Oct 2023 • Shuhan Wu, Huaiyu Wan, Wei Chen, Yuting Wu, Junfeng Shen, Youfang Lin
To address these issues, we propose a novel knowledge graph reasoning approach, the Relational rUle eNhanced Graph Neural Network (RUN-GNN).
no code implementations • 23 May 2023 • Yuting Wu, Qiwen Wang, Ziyu Wang, Xinxin Wang, Buvna Ayyagari, Siddarth Krishnan, Michael Chudzik, Wei D. Lu
The efficacy of training larger models is evaluated using realistic hardware parameters and shows that that analog CIM modules can enable efficient mix-precision DNN training with accuracy comparable to full-precision software trained models.
no code implementations • 13 Apr 2023 • Ziyu Wang, Yuting Wu, Yongmo Park, Sangmin Yoo, Xinxin Wang, Jason K. Eshraghian, Wei D. Lu
Analog compute-in-memory (CIM) systems are promising for deep neural network (DNN) inference acceleration due to their energy efficiency and high throughput.
no code implementations • 15 Oct 2022 • Yinger Zhang, Zhouyi Wu, Peiying Lin, Yang Pan, Yuting Wu, Liufang Zhang, Jiangtao Huangfu
It is created specifically for raw video captured by a lensless camera and has the ability to properly extract and combine temporal and spatial features.
no code implementations • 9 Oct 2022 • Yinger Zhang, Zhouyi Wu, Peiying Lin, Yuting Wu, Lusong Wei, Zhengjie Huang, Jiangtao Huangfu
Lensless cameras are characterized by several advantages (e. g., miniaturization, ease of manufacture, and low cost) as compared with conventional cameras.
1 code implementation • Findings (ACL) 2021 • Shuang Zeng, Yuting Wu, Baobao Chang
However, not all entity pairs can be connected with a path and have the correct logical reasoning paths in their graph.
Ranked #19 on Relation Extraction on DocRED
1 code implementation • NAACL 2021 • Xiao Liu, Da Yin, Yansong Feng, Yuting Wu, Dongyan Zhao
Causal inference is the process of capturing cause-effect relationship among variables.
1 code implementation • ACL 2020 • Yuting Wu, Xiao Liu, Yansong Feng, Zheng Wang, Dongyan Zhao
This paper presents Neighborhood Matching Network (NMN), a novel entity alignment framework for tackling the structural heterogeneity challenge.
1 code implementation • IJCNLP 2019 • Yuting Wu, Xiao Liu, Yansong Feng, Zheng Wang, Dongyan Zhao
Entity alignment is a viable means for integrating heterogeneous knowledge among different knowledge graphs (KGs).
Ranked #18 on Entity Alignment on DBP15k zh-en (using extra training data)
1 code implementation • 22 Aug 2019 • Yuting Wu, Xiao Liu, Yansong Feng, Zheng Wang, Rui Yan, Dongyan Zhao
Entity alignment is the task of linking entities with the same real-world identity from different knowledge graphs (KGs), which has been recently dominated by embedding-based methods.
Ranked #20 on Entity Alignment on DBP15k zh-en (using extra training data)
no code implementations • Neurocomputing 2018 • Yuting Wu, Mei Yuan, Shaopeng Dong, Li Lin, Yingqi Liu b
Following that, this paper aims to propose utilizing vanilla LSTM neural networks to get good RUL prediction accuracy which makes the most of long short-term memory ability, in the cases of complicated operations, working conditions, model degradations and strong noises.
no code implementations • 14 Feb 2014 • Andrew Gordon Wilson, Yuting Wu, Daniel J. Holland, Sebastian Nowozin, Mick D. Mantle, Lynn F. Gladden, Andrew Blake
Nuclear magnetic resonance (NMR) spectroscopy exploits the magnetic properties of atomic nuclei to discover the structure, reaction state and chemical environment of molecules.