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We present KBLRN, a framework for end-to-end learning of knowledge base representations from latent, relational, and numerical features.
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Reasoning with neural tensor networks for knowledge base completion
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Z. Wang, J. Zhang, J. Feng, and Z. Chen · 2014
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Representing text for joint embedding of text and knowledge bases
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A. Garcia-Duran, A. Bordes, N. Usunier, and Y. Grandvalet · 2015
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T. Rocktäschel, S. Singh, and S. Riedel · 2015
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Observed versus latent features for knowledge base and text inference
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Convolutional 2d knowledge graph embeddings
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Embedding multimodal relational data
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Modeling relational data with graph convolutional networks
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