本文前置知识: GAT: 详见图神经网络入门. Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs本文是论文Learning

本文前置知识: GCN: 详见图神经网络入门 R - GCN: 详见R - GCN: Modeling Relational Data with Graph Convolutional Networks Composition-ba

Knowledge Graph Embedding Based Question Answering本文是论文Knowledge Graph Embedding Based Question Answering的阅读笔记和个人理解. Bas

本文前置知识: ConvE: 详见ConvE: Convolutional 2D Knowledge Graph Embeddings Contextual Parameter Generation for Knowledge Gr

本文前置知识: GNN: 详见图神经网络入门 Modeling Relational Data with Graph Convolutional Networks本文是论文Modeling Relational Data with

RotatE: Knowledge Grpah Embedding by Relational Rotation Complex Space本文是论文ROTATE: KNOWLEDGE GRAPH EMBEDDING BY RELATION

本文前置知识: GNN: 详见图神经网络入门 ConvE: 详见ConvE: Convolutional 2D Knowledge Graph Embeddings ConvKB: 详见ConvKB: A Novel Embedding

本文前置知识: Transformer: 详见Transformer精讲 BERT: 详见ELMo, GPT, BERT Pytorch实现: Transformer 2022.04.03: 修正Pre Norm效果好于Post No

本文前置知识: ConvE: 详见ConvE: Convolutional 2D Knowledge Graph Embeddings ConvR: Adaptive Convolution for Multi-Relational

2021.03.09: 修正关于引入逆三元组的影响. 2021.04.18: 更新一篇更早的类似论文GAKE. LightCAKE: A Lightweight Framework for Context-Aware Knowledge

本文前置知识: 图结构基础知识(数据结构相关内容, 自行查阅). 2021.04.06: 更新GraphSAGE的理解. Introduction: Graph Neural Network本文介绍的是GNN方面入门级别的知识, 其

ConvBERT: Improving BERT with Span-based Dynamic Convolution 本文前置知识: Light Weight Convolution: 详见基于轻量级卷积和动态卷积替代的注意力机制.