School of Computing

Publications by Dr Marek Grzes

Also view these in the Kent Academic Repository

Article
Champion, T., Grzes, M. and Bowman, H. (2022) "Branching Time Active Inference with Bayesian Filtering", Neural Computation. MIT Press.
Champion, T., Da Costa, L., Bowman, H. and Grześ, M. (2022) "Branching Time Active Inference: The theory and its generality", Neural Networks. Elsevier, pp. 295-316. doi: 10.1016/j.neunet.2022.03.036.
Champion, T., Grześ, M. and Bowman, H. (2021) "Realising Active Inference in Variational Message Passing: the Outcome-blind Certainty Seeker", Neural Computation. MIT Press. doi: 10.1162/neco_a_01422.
Casey, A., Azhar, H., Grzes, M. and Sakel, M. (2019) "BCI controlled robotic arm as assistance to the rehabilitation of neurologically disabled patients", Disability and Rehabilitation: Assistive Technology. Taylor & Francis. doi: 10.1080/17483107.2019.1683239.
Vallati, M., Chrpa, L., Grzes, M., McCluskey, T. L., Roberts, M. and Sanner, S. (2015) "The 2014 International Planning Competition: Progress and Trends", AI Magazine. AAAI, pp. 90-98. doi: http://dx.doi.org/10.1609/aimag.v36i3.2571.
Grześ, M., Poupart, P., Yang, X. and Hoey, J. (2014) "Energy Efficient Execution of POMDP Policies", IEEE Transactions on Cybernetics. IEEE, pp. 2484-2497. doi: 10.1109/TCYB.2014.2375817.
Czajkowski, M., Grzes, M. and Kretowski, M. (2014) "Multi-test Decision Tree and its Application to Microarray Data Classification", Artificial Intelligence in Medicine. Elsevier, pp. 35-44. doi: 10.1016/j.artmed.2014.01.005.
Grzes, M., Hoey, J., Khan, S. S., Mihailidis, A., Czarnuch, S., Jackson, D. and Monk, A. (2014) "Relational approach to knowledge engineering for POMDP-based assistance systems as a translation of a psychological model", International Journal of Approximate Reasoning, pp. 36-58. doi: doi:10.1016/j.ijar.2013.03.006.
Book section
Liza, F. F. and Grzes, M. (2016) "An Improved Crowdsourcing Based Evaluation Technique for Word Embedding Methods", in Proceedings of the 1st Workshop on Evaluating Vector-Space Representations for NLP. The First Workshop on Evaluating Vector Space Representations for NLP (RepEval at ACL), Stroudsburg, Pennsylvania, USA: Association for Computational Linguistics, pp. 55-61.
Grzes, M., Poupart, P. and Hoey, J. (2013) "Controller Compilation and Compression for Resource Constrained Applications", in Perny, P., Pirlot, M., and Tsoukias, A. (eds.) Algorithmic Decision Theory Third International Conference. International Conference on Algorithmic Decision Theory (ADT), Berlin, Germany: Springer, pp. 193-207. doi: 10.1007/978-3-642-41575-3_15.
Conference or workshop item
Sawicki, P., Grzes, M., Jordanous, A., Brown, D. and Peeperkorn, M. (2022) "Training GPT-2 to represent two Romantic-era authors: challenges, evaluations and pitfalls", in. 13th International Conference on Computational Creativity.
Bonheme, L. and Grzes, M. (2020) "SESAM at SemEval-2020 Task 8: Investigating the relationship between image and text in sentiment analysis of memes", in. 14th International Workshop on Semantic Evaluation (SemEval-2020). Available at: https://aclanthology.org/2020.semeval-1.102/.
Harris, L. and Grzes, M. (2019) "Comparing Explanations between Random Forests and Artificial Neural Networks", in. 2019 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2019), IEEE. doi: 10.1109/SMC.2019.8914321.
Liza, F. F. and Grzes, M. (2019) "Relating RNN layers with the spectral WFA ranks in sequence modelling", in. ACL workshop on Deep Learning and Formal Languages: Building Bridges.
de Lemos, R. and Grzes, M. (2019) "Self-adaptive Artificial Intelligence", in. 2019 IEEE/ACM 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), New York, NY, USA: IEEE. doi: 10.1109/SEAMS.2019.00028.
Liza, F. F. and Grzes, M. (2018) "Improving Language Modelling with Noise Contrastive Estimation", in. The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), Palo Alto, California, USA: AAAI Press, pp. 5277-5284. Available at: https://aaai.org/Library/AAAI/aaai18contents.php.
Grzes, M. (2017) "Reward Shaping in Episodic Reinforcement Learning", in. Sixteenth International Conference on Autonomous Agents and Multiagent Sytems (AAMAS 2017), ACM, pp. 565-573. Available at: https://dl.acm.org/citation.cfm?id=3091208&CFID=832062567&CFTOKEN=79662490.
Liza, F. F. and Grzes, M. (2016) "A Spectral Method that Worked Well in the SPiCe'16 Competition", in Verwer, S., van Zaanen, M., and Smetsers, R. (eds.). The 13th International Conference on Grammatical Inference, Journal of Machine Learning Research, pp. 143-148. Available at: http://www.jmlr.org/proceedings/papers/v57/.
Liza, F. F. and Grzes, M. (2016) "Estimating the Accuracy of Spectral Learning for HMMs", in. The 17th International Conference on Artificial Intelligence: Methodology, Systems, Applications (AIMSA), Springer, pp. 46-56. doi: 10.1007/978-3-319-44748-3_5.
Grzes, M. and Poupart, P. (2015) "Incremental Policy Iteration with Guaranteed Escape from Local Optima in POMDP Planning", in. International Conference on Autonomous Agents and Multiagent Systems (AAMAS). Available at: http://www.aamas2015.com/en/AAMAS_2015_USB/aamas/p1249.pdf.
Grzes, M. and Poupart, P. (2014) "POMDP Planning and Execution in an Augmented Space", in. International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 757-764. Available at: http://www.aamas-conference.org/Proceedings/aamas2014/aamas/p757.pdf.
Grzes, M., Poupart, P. and Hoey, J. (2013) "Isomorph-Free Branch and Bound Search for Finite State Controllers", in. International Joint Conference on Artificial Intelligence (IJCAI). Available at: http://www.aaai.org/ocs/index.php/IJCAI/IJCAI13/paper/view/6954.
Grzes, M. and Hoey, J. (2013) "On the Convergence of Techniques that Improve Value Iteration", in. International Joint Conference on Neural Networks (IJCNN), pp. 1-8. doi: 10.1109/IJCNN.2013.6706982.
Total publications in KAR: 23 [See all in KAR]

School of Computing, University of Kent, Canterbury, Kent, CT2 7NF

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Last Updated: 28/09/2022