Abstract: Knowledge Graph Embedding (KGE) aims to learn dense embeddings as the representations for entities and relations in KGs. Indeed, the entities in existing KGs suffer from the data imbalance ...

Abstract: Knowledge Graphs (KGs), with their intricate hierarchies and semantic ... In particular, SimE is competitive with state-of-the-art KG embedding models and is able to achieve high values of ...

Cambium Networks has announced it is collaborating with Facebook on high-speed connectivity solutions using Terragraph. Terragraph connectivity technology will be embedded in Cambium Networks’ ...

This is a pure Python implementation of knowledge graph embedding (KGE) methods in TensorFlow 1.x/Keras, which was part of our experiments to unify previous KGE models under the perspective in our ...

graph_rag <- Source code for use in this project. │ ├── __init__.py <- Makes graph_rag a Python module │ ├── config.py <- Store useful variables and configuration │ ├── dataset.py <- Scripts to ...

This approach relies on embedding trained machine learning models within the overall optimization formulation in place of complicated nonlinear equations describing the physics, costing, and ...

School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, U.K. Food Colloids and Bioprocessing Group, School of Food Science and Nutrition, University of Leeds, Leeds LS2 9JT, ...

Beijing Institute of System Engineering, P.O.Box 9702-19, Beijing 100101, P. R. China ...