EMNLP 2018: HyTE: Hyperplane-based Temporally aware Knowledge Graph Embedding
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Updated
Jan 15, 2019 - Python
EMNLP 2018: HyTE: Hyperplane-based Temporally aware Knowledge Graph Embedding
Graph Attention Networks for Entity Summarization is the model that applies deep learning on graphs and ensemble learning on entity summarization tasks.
Combining Image Recognition with Knowledge Graph Embedding for Learning Semantic Attribute of Images
Source code for experiments in the papers "Beyond Benchmarks: Assessing Knowledge Graph Completion Methods on Non-Benchmark Employee Data" (IEEE 2024, yet to be published)
Combining Query Rewriting (PerfectRef) and Knowledge Graph Embeddings with Complex Query Answering
In- and post- process methods for optimizing explanations path based on newly defined quantitative explanation metrics
[Paper][Preprint 2024] Mixture of Modality Knowledge Experts for Robust Multi-modal Knowledge Graph Completion
Code for generating Linked Papers with Code a high-quality RDF knowledge graph with metadata about the machine learning landscape.
Jointly Learning knowledge graph Embedding, Fine Grain Entity Types and Language Modeling.
OpenKE-based implementation of KG embedding model JOIE (Jointly Embedding Instances and Ontological Concepts)
Experimental setup and results for 2021-2022 academic research "Effects of knowledge graph structural properties on their predictive performance".
Joint Multilingual Knowledge Graph Completion and Alignment (Findings of EMNLP 2022) (Pytorch)
Project on the use of Knowledge Graph Embeddings for use for a classification problem for Capstone Project submitted for the MSc of Data Analytics
Properly pre-processed full-scale Freebase datasets
Question-Answering (QA) System that leverages the power of Knowledge Graphs and Language Models
基于 OpenKE-PyTorch 开发的知识图谱嵌入工具包,支持跨平台运行,具备自动超参数搜索、高效并行训练以及实验结果记录功能,为研究与应用提供强大助力。
Graph Neural Network for Disease-Gene Link Prediction
A placeholder for my work in word embeddings and knowledge graph representations
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