24 citations · 53 across the 9 of their papers we have counts for
12 papers
Federated Dynamic GNN with Secure Aggregation
Meng Jiang, Taeho Jung, Ryan Karl +1
Given video data from multiple personal devices or street cameras, can we exploit the structural and dynamic information to learn dynamic representation of objects for applications…
Learning Attribute-Structure Co-Evolutions in Dynamic Graphs
Daheng Wang, Zhihan Zhang, Yihong Ma +4
Most graph neural network models learn embeddings of nodes in static attributed graphs for predictive analysis. Recent attempts have been made to learn temporal proximity of the no…
Calendar Graph Neural Networks for Modeling Time Structures in Spatiotemporal User Behaviors
Daheng Wang, Meng Jiang, Munira Syed +4
User behavior modeling is important for industrial applications such as demographic attribute prediction, content recommendation, and target advertising. Existing methods represent…
Canonicalizing Open Knowledge Bases with Multi-Layered Meta-Graph Neural Network
Tianwen Jiang, Tong Zhao, Bing Qin +3
Noun phrases and relational phrases in Open Knowledge Bases are often not canonical, leading to redundant and ambiguous facts. In this work, we integrate structural information (fr…
A Probabilistic Model with Commonsense Constraints for Pattern-based Temporal Fact Extraction
Yang Zhou, Tong Zhao, Meng Jiang
Textual patterns (e.g., Country's president Person) are specified and/or generated for extracting factual information from unstructured data. Pattern-based information extraction m…
Crossing Variational Autoencoders for Answer Retrieval
Wenhao Yu, Lingfei Wu, Qingkai Zeng +3
Answer retrieval is to find the most aligned answer from a large set of candidates given a question. Learning vector representations of questions/answers is the key factor. Questio…