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Found 2 papers, 1 papers with code
On the Complementary Nature of Knowledge Graph Embedding, Fine Grain Entity Types, and Language Modeling
We demonstrate the complementary natures of neural knowledge graph embedding, fine-grain entity type prediction, and neural language modeling.
Mixture Distributions for Scalable Bayesian Inference
We show Ensembles of deterministic and stochastic Neural Networks can indeed be cast as an approximate Bayesian inference.
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