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Number of items: 11.

Ager, Thomas, Kuzelka, Ondrej and Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881 2018. Modelling salient features as directions in fine-tuned semantic spaces. Presented at: SIGNLL Conference on Computational Natural Language Learning, Brussels, Belgium, 31 Oct - 1 Nov 2018.
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Kuzelka, Ondrej, Wang, Yuyi and Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881 2018. VC-dimension based generalization bounds for relational learning. Presented at: ECML-PKDD 2018: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Dublin, Ireland, 10-14 Sept 2018.
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Kuzelka, Ondrej, Wang, Yuyi, Davis, Jesse and Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881 2018. PAC-reasoning in relational domains. Presented at: UAI2018: 34th Conference on Uncertainty in Artificial Intelligence, Monterey, CA, USA, 6-10 August 2018.
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Sourek, Gustav, Aschenbrenner, Vojtech, Zelezny, Filip, Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881 and Kuzelka, Ondrej 2018. Lifted relational neural networks: efficient learning of latent relational structures. Journal of Artificial Intelligence Research 62 , pp. 69-100. 10.1613/jair.1.11203
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Gutierrez Basulto, Victor ORCID: https://orcid.org/0000-0002-6117-5459, Jung, Jean Christoph and Kuzelka, Ondrej 2018. Quantified Markov logic networks. Presented at: 16th International Conference on Principles of Knowledge Representation and Reasoning (KR-18), Tempe, Arizona, USA, 30 October-2 November 2018. International Conference on Principles of Knowledge Representation and Reasoning.
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Sourek, Gustav, Manandhar, Suresh, Zelezny, Filip, Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881 and Kuzelka, Ondrej 2017. Learning predictive categories using lifted relational neural networks. Presented at: ILP 2016: International Conference on Inductive Logic Programming, London, UK, 4-6 September 2016. Published in: Cussens, James and Russo, Alexandra eds. Inductive Logic Programming. Lecture Notes in Computer Science. Lecture Notes in Computer Science , vol.10326 Cham: Springer, pp. 108-119. 10.1007/978-3-319-63342-8_9
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Kuzelka, Ondrej, Davis, Jesse and Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881 2017. Induction of interpretable possibilistic logic theories from relational data. Presented at: International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, 19-26 August 2017.
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Kuzelka, Ondrej, Davis, Jesse and Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881 2016. Stratified knowledge bases as interpretable probabilistic models. Presented at: Interpretable ML for Complex Systems NIPS 2016 Workshop, Barcelona, Spain, 9 December 2016.
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Kuzelka, Ondrej, Davis, Jesse and Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881 2016. Interpretable encoding of densities using possibilistic logic. Presented at: 22nd European Conference on Artificial Intelligence, The Hague, 29 August - 2 September 2016.
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Ager, Thomas, Kuzelka, Ondrej and Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881 2016. Inducing symbolic rules from entity embeddings using auto-encoders. Presented at: Eleventh International Workshop on Neural-Symbolic Learning and Reasoning, New York; NY, 16-17 July 2016,
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Kuzelka, Ondrej, Davis, Jesse and Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881 2015. Encoding Markov logic networks in possibilistic logic. Presented at: 31st Conference on Uncertainty in Artificial Intelligence, Amsterdam, 12-16 July 2015.
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