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KBlrn: End-to-End Learning of Knowledge Base Representations with Latent, Relational, and Numerical Features.

, and . UAI, page 372-381. AUAI Press, (2018)

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KBLRN : End-to-End Learning of Knowledge Base Representations with Latent, Relational, and Numerical Features., and . CoRR, (2017)On embeddings as an alternative paradigm for relational learning., , and . CoRR, (2018)MMKG: Multi-modal Knowledge Graphs., , , , , and . ESWC, volume 11503 of Lecture Notes in Computer Science, page 459-474. Springer, (2019)Towards a Spectrum of Graph Convolutional Networks., and . DSW, page 244-248. IEEE, (2018)Learning Sequence Encoders for Temporal Knowledge Graph Completion., , and . EMNLP, page 4816-4821. Association for Computational Linguistics, (2018)KBlrn: End-to-End Learning of Knowledge Base Representations with Latent, Relational, and Numerical Features., and . UAI, page 372-381. AUAI Press, (2018)Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus, , , , , , and . (2016)cite arxiv:1603.06807Comment: 13 pages, 1 figure, 7 tables.Representation Learning for Visual-Relational Knowledge Graphs., , , , and . CoRR, (2017)Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus., , , , , , and . ACL (1), The Association for Computer Linguistics, (2016)Learning Graph Representations with Embedding Propagation., and . NIPS, page 5119-5130. (2017)