ConvE with 8 times less parameters is still more powerful than DistMult. Relational Graph Convolutional Networks use roughly 32x more parameters to have the same performance as ConvE.

Jul 5, 2017 · In this work, we introduce ConvE, a multi-layer convolutional network model for link prediction, and report state-of-the-art results for several established datasets.

An implementation of ConvE from [dettmers2018]. ConvE represents entities using a d -dimensional embedding and a scalar tail bias. Relations are represented by a d -dimensional vector. All three …

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Feb 2, 2018 · In this work we introduce ConvE, a multi-layer convolutional network model for link prediction, and report state-of-the-art results for several established datasets.

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Implementation of ConvE proposed by Dettmers et al. in Convolutional 2D Knowledge Graph Embeddings. You can find the official repository with knowledge graph datasets here.

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Convolutional 2D Knowledge Graph Embeddings resources - ConvE/main.py at master · TimDettmers/ConvE

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