33.1k citations · 35.3k across the 95 of their papers we have counts for
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AttrE2vec: Unsupervised Attributed Edge Representation Learning
Piotr Bielak, Tomasz Kajdanowicz, Nitesh V. Chawla
Representation learning has overcome the often arduous and manual featurization of networks through (unsupervised) feature learning as it results in embeddings that can apply to a…
Network analysis of ballast-mediated species transfer reveals important introduction and dispersal patterns in the Arctic
Mandana Saebi, Jian Xu, Salvatore R. Curasi +3
Rapid climate change has wide-ranging implications for the Arctic region, including sea ice loss, increased geopolitical attention, and expanding economic activity, including a dra…
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…
Jointly Predicting Job Performance, Personality, Cognitive Ability, Affect, and Well-Being
Pablo Robles-Granda, Suwen Lin, Xian Wu +15
Assessment of job performance, personalized health and psychometric measures are domains where data-driven and ubiquitous computing exhibits the potential of a profound impact in t…