Search Results for author:
Found 10 papers, 2 papers with code
Knowledge Graph Embedding: An Overview
We will also discuss an emerging approach for KG completion which leverages pre-trained language models (PLMs) and textual descriptions of entities and relations and offer insights into the integration of KGE embedding methods with PLMs for KG completion.
AsyncET: Asynchronous Learning for Knowledge Graph Entity Typing with Auxiliary Relations
Previously, KG embedding (KGE) methods tried to solve the KGET task by introducing an auxiliary relation, 'hasType', to model the relationship between entities and their types.
Knowledge Graph Embedding with 3D Compound Geometric Transformations
The cascade of 2D geometric transformations were exploited to model relations between entities in a knowledge graph (KG), leading to an effective KG embedding (KGE) model, CompoundE.
Ranked #7 on
Link Property Prediction
on ogbl-wikikg2
GreenKGC: A Lightweight Knowledge Graph Completion Method
Knowledge graph completion (KGC) aims to discover missing relationships between entities in knowledge graphs (KGs).
Ranked #21 on
Link Prediction
on FB15k-237
CompoundE: Knowledge Graph Embedding with Translation, Rotation and Scaling Compound Operations
Since translation, rotation, and scaling operations are cascaded to form a compound one, the new model is named CompoundE.
Accelerated Design and Deployment of Low-Carbon Concrete for Data Centers
Finally, we report on how these formulations were used in the construction of buildings and structures in a Meta data center in DeKalb, IL, USA.
CORE: A Knowledge Graph Entity Type Prediction Method via Complex Space Regression and Embedding
A new KG entity type prediction method, named CORE (COmplex space Regression and Embedding), is proposed in this work.
KGBoost: A Classification-based Knowledge Base Completion Method with Negative Sampling
Knowledge base completion is formulated as a binary classification problem in this work, where an XGBoost binary classifier is trained for each relation using relevant links in knowledge graphs (KGs).
FaceHop: A Light-Weight Low-Resolution Face Gender Classification Method
For gray-scale face images of resolution $32 \times 32$ in the LFW and the CMU Multi-PIE datasets, FaceHop achieves correct gender classification rates of 94. 63% and 95. 12% with model sizes of 16. 9K and 17. 6K parameters, respectively.
Accelerated Discovery of Sustainable Building Materials
Concrete is the most widely used engineered material in the world with more than 10 billion tons produced annually.
