4 papers · 1 filter
Integrating Meta-Features with Knowledge Graph Embeddings for Meta-Learning
Antonis Klironomos, Ioannis Dasoulas, Francesco Periti +4
The vast collection of machine learning records available on the web presents a significant opportunity for meta-learning, where past experiments are leveraged to improve performan…
Improving Knowledge Graph Embeddings through Contrastive Learning with Negative Statements
Rita T. Sousa, Heiko Paulheim
Knowledge graphs represent information as structured triples and serve as the backbone for a wide range of applications, including question answering, link prediction, and recommen…
Bio-KGvec2go: Serving up-to-date Dynamic Biomedical Knowledge Graph Embeddings
Hamid Ahmad, Heiko Paulheim, Rita T. Sousa
Knowledge graphs and ontologies represent entities and their relationships in a structured way, having gained significance in the development of modern AI applications. Integrating…
Multi-dataset and Transfer Learning Using Gene Expression Knowledge Graphs
Rita T. Sousa, Heiko Paulheim
Gene expression datasets offer insights into gene regulation mechanisms, biochemical pathways, and cellular functions. Additionally, comparing gene expression profiles between dise…