#graphembedding — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #graphembedding, aggregated by home.social.
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Very proud to see Guillaume and Ndeye-Emilie, two of my PhD students, awarded at #ESWC2026! Congratulations to them!
#ESWC2026 #MachineLearning #KnowledgeGraph #SemanticWeb #NLP #LowResourceLanguages #GraphEmbedding #ArtificialIntelligence #linkPrediction
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Treat Different Negatives Differently: Enriching Loss Functions with Domain and Range Constraints for Link Prediction
https://2024.eswc-conferences.org/wp-content/uploads/2024/04/146640020.pdf#knowledgeGraph #syntheticData #neuroSymbolicAI #ArtificialIntelligence #semanticWeb #linkPrediction #graphEmbedding
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PyGraft: Configurable Generation of Synthetic Schemas and Knowledge Graphs at Your Fingertips https://2024.eswc-conferences.org/wp-content/uploads/2024/04/146640336-1.pdf
#knowledgeGraph #syntheticData #neuroSymbolicAI #ArtificialIntelligence #semanticWeb #linkPrediction #graphEmbedding
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Very glad to announce that we got 2 best paper awards at #ESWC2024 for our works about PyGraft (resource track) and semantically enhanced loss functions to learn graph #embedding (research track)! Congratulations Nicolas Hubert!
#knowledgeGraph #syntheticData #neuroSymbolicAI #ArtificialIntelligence #semanticWeb #linkPrediction #graphEmbedding
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Thrilled to share two articles I co-authored for the 1st issue of Transactions on Graph Data and Knowledge (@tgdkjournal):
- #MachineLearning and #KnowledgeGraphs: Existing Gaps and Future Research Challenges (https://doi.org/10.4230/TGDK.1.1.8)
- #KnowledgeGraphs for the #LifeSciences: Recent Developments, Challenges and Opportunities (https://doi.org/10.4230/TGDK.1.1.5)
It was a fantastic experience to collaborate on these two vision papers!
#semanticWeb #linkedOpenData #explainableAI #graphEmbedding -
Proud to announce our new paper, "Relevant Entity Selection: Knowledge Graph Bootstrapping via Zero-Shot Analogical Pruning" with Lucas Jarnac and Miguel Couceiro, accepted in #cikm2023
#knowledgeGraph #machineLearning #graphEmbedding #transferLearning #zeroShot #openScience