150 citations · 208 across the 10 of their papers we have counts for
10 papers
A Comprehensive Study on Knowledge Graph Embedding over Relational Patterns Based on Rule Learning
Long Jin, Zhen Yao, Mingyang Chen +2
Knowledge Graph Embedding (KGE) has proven to be an effective approach to solving the Knowledge Graph Completion (KGC) task. Relational patterns which refer to relations with speci…
Information compression via hidden subgroup quantum autoencoders
Feiyang Liu, Kaiming Bian, Fei Meng +2
We design a quantum method for classical information compression that exploits the hidden subgroup quantum algorithm. We consider sequence data in a database with a priori unknown…
Neural-Symbolic Entangled Framework for Complex Query Answering
Zezhong Xu, Wen Zhang, Peng Ye +2
Answering complex queries over knowledge graphs (KG) is an important yet challenging task because of the KG incompleteness issue and cascading errors during reasoning. Recent query…
Ruleformer: Context-aware Differentiable Rule Mining over Knowledge Graph
Zezhong Xu, Peng Ye, Hui Chen +3
Rule mining is an effective approach for reasoning over knowledge graph (KG). Existing works mainly concentrate on mining rules. However, there might be several rules that could be…
PKGM: A Pre-trained Knowledge Graph Model for E-commerce Application
Wen Zhang, Chi-Man Wong, Ganqinag Ye +4
In recent years, knowledge graphs have been widely applied as a uniform way to organize data and have enhanced many tasks requiring knowledge. In online shopping platform Taobao, w…
Insight-HXMT observations of Swift J0243.6+6124: the evolution of RMS pulse fractions at super-Eddington luminosity
P. J. Wang, L. D. Kong, S. Zhang +116
Based on Insight-HXMT data, we report on the pulse fraction evolution during the 2017-2018 outburst of the newly discovered first Galactic ultraluminous X-ray source (ULX) Swift J0…
CVPR 2019 WAD Challenge on Trajectory Prediction and 3D Perception
Sibo Zhang, Yuexin Ma, Ruigang Yang
This paper reviews the CVPR 2019 challenge on Autonomous Driving. Baidu's Robotics and Autonomous Driving Lab (RAL) providing 150 minutes labeled Trajectory and 3D Perception datas…
Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs
Mingyang Chen, Wen Zhang, Wei Zhang +2
Link prediction is an important way to complete knowledge graphs (KGs), while embedding-based methods, effective for link prediction in KGs, perform poorly on relations that only h…
Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning
Wen Zhang, Bibek Paudel, Liang Wang +5
Reasoning is essential for the development of large knowledge graphs, especially for completion, which aims to infer new triples based on existing ones. Both rules and embeddings c…
Interaction Embeddings for Prediction and Explanation in Knowledge Graphs
Wen Zhang, Bibek Paudel, Wei Zhang +2
Knowledge graph embedding aims to learn distributed representations for entities and relations, and is proven to be effective in many applications. Crossover interactions --- bi-di…