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Results: 6
Number of items: 6
  • Open Access
    Younesian, T., Daza, D., van Krieken, E., Thanapalasingam, T., & Bloem, P. (2025). GRAPES: Learning to Sample Graphs for Scalable Graph Neural Networks. Transactions on Machine Learning Research, 2025, Article 3923. https://doi.org/10.48550/arXiv.2310.03399
  • 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
  • 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
  • Open Access
    van Krieken, E., Thanapalasingam, T., Tomczak, J. M., van Harmelen, F., & ten Teije, A. (2023). A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference. In A. Oh, T. Naumann, A. Globerson, K. Saenko, M. Hardt, & S. Levine (Eds.), 37th Conference on Neural Information Processing Systems (NeurIPS 2023): 10-16 December 2023, New Orleans, Louisana, USA (Advances in Neural Information Processing Systems; Vol. 36). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper_files/paper/2023/hash/4d9944ab3330fe6af8efb9260aa9f307-Abstract-Conference.html
  • Open Access
    Alivanistos, D., Báez Santamaría, S., Cochez, M., Kalo, J.-C., van Krieken, E., & Thanapalasingam, T. (2022). Prompting as Probing: Using Language Models for Knowledge Base Construction. In S. Singhania, T.-P. Nguyen, & S. Razniewski (Eds.), Proceedings of the Semantic Web Challenge on Knowledge Base Construction from Pre-trained Language Models 2022: co-located with the 21st International Semantic Web Conference (ISWC2022) : virtual event, Hanghzou, China, October 2022 (pp. 11-34). (CEUR Workshop Proceedings; Vol. 3274). CEUR-WS. https://ceur-ws.org/Vol-3274/paper2.pdf
  • Open Access
    Thanapalasingam, T., van Berkel, L., Bloem, P., & Groth, P. (2022). Relational graph convolutional networks: a closer look. PeerJ Computer Science, 8, Article e1073. https://doi.org/10.7717/PEERJ-CS.1073
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