Learning knowledge graph embeddings by deep relational roto-reflection

Dropout: a simple way to prevent neural networks from overfitting

Nitish Srivastava, Geoffrey E. Hinton, Alex Krizhevsky et al. · 2014 · 34.3K citations

Computing, Computer Science, Artificial Intelligence +12

Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-Equivalent APIs in Open-Source Repositories

Dagstuhl Research Online Publication Server · 2025 · 16.2K citations · Full text

Computing, Computer Science, Feature Engineering +16

Proceedings of the 19th International Joint Conference on Artificial Intelligence

Josep M. Pujol, Jordi Delgado, Ramón Sangüesa et al. · International Joint Conference on Artificial Intelligence · 2005 · 5.8K citations

Computing, Computer Science, Artificial Intelligence +11

Return of the Devil in the Details: Delving Deep into Convolutional Nets

Ken Chatfield, Karen Simonyan, Andrea Vedaldi et al. · 2014 · 3.1K citations

Computing, Computer Science, Computer Vision +11

Knowledge Graph Embedding: A Survey of Approaches and Applications

Quan Wang, Zhendong Mao, Bin Wang et al. · IEEE Transactions on Knowledge and Data Engineering · 2017 · 2.7K citations

Computing, Computer Science, Knowledge Capture +16