12 Publikationen
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2020 | Bielefelder E-Dissertation | PUB-ID: 2943362Panzner, M. (2020). Learning action models by curiosity driven self exploration and language guided generalization. Bielefeld: Universität Bielefeld. https://doi.org/10.4119/unibi/2943362
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2019 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2933998Panzner, M., Cimiano, P., & Gaspers, J. (2019). Modelling the co-emergence of linguistic constructions and action concepts: the case of action verbs. IEEE Transactions on Cognitive and Developmental Systems, 11(3), 435-449. doi:10.1109/TCDS.2019.2900418
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2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2911974Panzner, M., & Cimiano, P. (2017). A Deep Reinforcement Learning Based Model Supporting Object Familiarization. Proceedings of the 7th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics Lisbon, Portugal. doi:10.1109/DEVLRN.2017.8329828
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2017 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2914356Panzner, M., & Cimiano, P. (2017). A Deep Reinforcement Learning Based Model Supporting Object Familiarization. Presented at the International Conference on Development and Learning and on Epigenetic Robotics, Instituto Superior Tecnico (IST), Lisbon, Portugal.
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2016 | Datenpublikation | PUB-ID: 2904362Panzner, M. (2016). TLS Dataset. Bielefeld University. doi:10.4119/unibi/2904362
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2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2903474Panzner, M., & Cimiano, P. (2016). Comparing Hidden Markov Models and Long Short Term Memory Neural Networks for Learning Action Representations. In P. M. Pardalos, P. Conca, G. Giuffrida, & G. Nicosia (Eds.), Lecture Notes in Computer Science: Vol. 10122. Machine Learning, Optimization, and Big Data : Second International Workshop, MOD 2016, Volterra, Italy, August 26-29, 2016. Revised Selected Papers (pp. 94-105). Cham: Springer International Publishing. doi:10.1007/978-3-319-51469-7_8
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2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2659127Gaspers, J., Panzner, M., Lemme, A., Cimiano, P., Rohlfing, K., & Wrede, S. (2014). A multimodal corpus for the evaluation of computational models for (grounded) language acquisition. EACL Workshop on Cognitive Aspects of Computational Language Learning
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