Python implementation of "Data-dependent Learning of Symmetric/Antisymmetric Relations for Knowledge Base Completion [Manabe+. 2018]"
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Updated
Feb 25, 2018 - Python
Python implementation of "Data-dependent Learning of Symmetric/Antisymmetric Relations for Knowledge Base Completion [Manabe+. 2018]"
DeepPath - A Deep Reinforcement Learning Method for Knowledge Graph Reasoning using TensorForce
Code for "KBGAN: Adversarial Learning for Knowledge Graph Embeddings" https://arxiv.org/abs/1711.04071
EMNLP 2018: HyTE: Hyperplane-based Temporally aware Knowledge Graph Embedding
Code of the paper: Cross-lingual Knowledge Graph Alignment via Graph Convolutional Networks.
Simple-Question Answering based on Knowledge Graph Embeddings (part of my Ph.D. work)
SimplE Embedding for Link Prediction in Knowledge Graphs
Source code and datasets for EMNLP 2019 paper: Jointly Learning Entity and Relation Representations for Entity Alignment.
Combining Image Recognition with Knowledge Graph Embedding for Learning Semantic Attribute of Images
Implementations of Embedding-based methods for Knowledge Base Completion tasks
Jointly Learning knowledge graph Embedding, Fine Grain Entity Types and Language Modeling.
Role-Aware Modeling for N-ary Relational Knowledge Bases
The code of paper Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction. Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, Jie Wang. AAAI 2020.
A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization (NAACL 2019)
🪑 Benchmark the bloom filterer at https://pykeen.github.io/bloom-filterer-benchmark/
A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network (NAACL 2018) (Pytorch and Tensorflow)
Machine Learning (ML) algorithms need data in the form of feature vectors and class labels to come up with a trained model and predict new instances with that trained model. Data stored in Knowledge Graph(s) (KG) is in the form of triples. To apply ML algorithms on KG, we need to convert the individuals in the learning problem into feature vecto…
This repository contains our implementation of paper Hyperbolic Knowledge Graph Embedding in Extended Poincaré Ball. Xingchen Zhou, Peng Wang, Zhe Pan.
A TensorFlow-based implementation of knowledge graph embedding models.
Graph Neural Networks for Knowledge Graph Link Prediction (WSDM 2022) (Pytorch)
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