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Results: 125
Number of items: 125
  • Open Access
    Karabulut, E., Pileggi, S. F., Groth, P., & Degeler, V. (2024). Ontologies in Digital Twins: A Systematic Literature Review. Future Generation Computer Systems, 153, 442-456. https://doi.org/10.1016/j.future.2023.12.013
  • Open Access
    Zhang, Z., Groth, P., Calixto, I., & Schelter, S. (2024). Directions Towards Efficient and Automated Data Wrangling with Large Language Models. In 2024 IEEE 40th International Conference on Data Engineering Workshops: ICDEW 2024 : 13-17 May 2024, Utrecht, Netherlands : proceedings (pp. 301-304). IEEE Computer Society. https://doi.org/10.1109/ICDEW61823.2024.00044
  • Thanapalasingam, T., van Krieken, E., Bloem, P., & Groth, P. (2023, April 13). IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8039857
  • Karabulut, E., Pileggi, S. F., Groth, P., & Degeler, V. (2023, July 21). Data and Statistics for the SLR entitled "Ontologies in Digital Twins: A Systematic Literature Review" [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8172341
  • Thanapalasingam, T., van Krieken, E., Bloem, P., & Groth, P. (2023, April). IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14787483
  • Open Access
    Prieto, L., Den Boef, J., Groth, P., & Cornelisse, J. (2023). Parameter Efficient Node Classification on Homophilic Graphs. Transactions on Machine Learning Research, 2023, Article 640. https://openreview.net/forum?id=LIT8tjs6rJ
  • Open Access
    Grafberger, S., Groth, P., & Schelter, S. (2023). Automating and Optimizing Data-Centric What-If Analyses on Native Machine Learning Pipelines. Proceedings of the ACM on Management of Data, 1(2), Article 128. https://doi.org/10.1145/3589273
  • Open Access
    Jullien, S., Ariannezhad, M., Groth, P., & de Rijke, M. (2023). A Simulation Environment and Reinforcement Learning Method for Waste Reduction. Transactions on Machine Learning Research, 2023, Article 769. https://openreview.net/forum?id=KSvr8A62MD
  • Open Access
    Simperl, E., Groth, P., Staab, S., Sabou, M., Blomqvist, E., & Allen, B. (2023). Knowledge Engineering with Language Models and Neural Methods. Dagstuhl Reports, 12(9), 93-96. https://doi.org/10.4230/DagRep.12.9.60
  • Open Access
    Polat, F., Tiddi, I., Groth, P., & Vossen, P. (2023). Improving Graph-to-Text Generation Using Cycle Training. In S. Carvalho, A. F. Khan, A. Ostroški Anić, B. Spahiu, J. Gracia, J. P. McCrae, D. Gromann, B. Heinisch, & A. Salgado (Eds.), Language, data and knowledge 2023: LDK 2023 : proceedings of the 4th Conference on Language, Data and Knowledge : 12-15 September 2023, Vienna, Austria (pp. 256-261). NOVA CLUNL. https://doi.org/10.34619/srmk-injj
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