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

Very happy to announce our new paper accepted in @eswc_conf
#ESWC2024: "Treat Different Negatives Differently: Enriching Loss Functions with Domain and Range Constraints for Link Prediction"!

📎 https://arxiv.org/pdf/2303.00286.pdf

w/ N. Hubert, A. Brun, and D. Monticolo

#knowledgeGraph #semanticWeb #machineLearning #linkPrediction #neurosymbolicAI #artificialIntelligence #linkedOpenData #graphEmbeddings #embeddings #graphNeuralNetworks

Our paper "PyGraft: Configurable Generation of Synthetic #Schemas and #KnowledgeGraphs at Your Fingertips" has been accepted in @eswc_conf #ESWC2024!

Paper: https://arxiv.org/pdf/2309.03685.pdf
Code: https://github.com/nicolas-hbt/pygraft

PyGraft is a configurable #Python tool to generate both synthetic #schemas and #knowledgeGraphs easily, supporting several RDFS and OWL constructs. These #datasets are useful for, e.g., #neurosymbolicAI, #linkPrediction, #nodeClassification, #nodeClustering, #ontology repairing

2nd add on to our free MOOC lecture series on #KnowledgeGraphs is a colab notebook on knowledge graph completion with TransE through which my colleagues Ann Tan and @MahsaVafaie will guide you in the video.
#OpenHPI video: https://open.hpi.de/courses/knowledgegraphs2023/items/48Sn5Tr9RKo24RXu7OwgOz
youtube video: https://www.youtube.com/watch?v=IVTVzgCbHOw&list=PLNXdQl4kBgzubTOfY5cbtxZCgg9UTe-uF&index=67
colab notebook: https://colab.research.google.com/drive/104ad-kusmzfYgkK_L8ETWUAjfdreE9e2#scrollTo=fQ08XPbaZgQ4

@fizise @fiz_karlsruhe #semanticweb #kge #embeddings #linkprediction #videolecture #video