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  2. van Waarde, H., Tesi, P., & Camlibel, M. (2018). Topology reconstruction of dynamical networks via constrained Lyapunov equations. 115-115. Abstract from 37th Benelux meeting on Systems and Control, Soesterberg, Netherlands.
  3. Reyes Báez, R., van der Schaft, A., & Jayawardhana, B. (2018). Virtual differential passivity based control of mechanical systems in the port-Hamiltonian framework. 100-100. Abstract from 37th Benelux meeting on Systems and Control, Soesterberg, Netherlands.
  4. Francalanza, A., Pérez, J. A., & Sánchez, C. (2018). Runtime Verification for Decentralised and Distributed Systems. In E. Bartocci, & Y. Falcone (Eds.), Lectures on Runtime Verification (pp. 176-210). Springer. https://doi.org/10.1007/978-3-319-75632-5_6
  5. Sabatelli, M., Bidoia, F., Codreanu, V., & Wiering, M. (2018). Learning to Evaluate Chess Positions with Deep Neural Networks and Limited Lookahead. Paper presented at 7th International Conference on Pattern Recognition Applications and Methods, Madeira, Portugal.
  6. Bu, Y. (2018). A class of linear solvers based on multilevel and supernodal factorization. [Groningen]: University of Groningen.
  7. Paul, K., & Cnossen, F. (2018). A Cognitive Neuroscience Perspective on Skill Acquisition in Catheter-based Interventions. In P. Lanzer (Ed.), Textbook of Catheter-Based Cardiovascular Interventions Springer Nature. https://doi.org/10.1007/978-3-319-55994-0
  8. Bidoia, F., Sabatelli, M., Shantia, A., Wiering, M. A., & Schomaker, L. (2018). A Deep Convolutional Neural Network for Location Recognition and Geometry based Information. In M. De Marsico, G. Sanniti di Baja, & A. Fred (Eds.), Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods (pp. 27-36). SciTePress. https://doi.org/10.5220/0006542200270036
  9. Ampatzoglou, A., Michailidis, A., Sarikyriakidis, C., Ampatzoglou, A., Chatzigeorgiou, A., & Avgeriou, P. (2018). A Framework for Managing Interest in Technical Debt: An Industrial Validation. In Proceedings of the 2018 International Conference on Technical Debt (pp. 115-124). (TechDebt '18). New York, NY, USA: ACM Press. https://doi.org/10.1145/3194164.3194175
  10. Verstappen, R. (2018). A minimum-relaxation model for large eddy simulation. 255-261 . Paper presented at Proceedings of the TI 2015 Conference, Cargèse, Corsica, France. https://doi.org/10.1007/978-3-319-60387-2_28
  11. Jiao, J., Trentelman, H., & Camlibel, M. (2018). A suboptimality approach to distributed H-2 optimal control. In K. Camlibel, & H. Shim (Eds.), Proceedings of the 7th IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys18), August 27-28, Groningen, The Netherlands (pp. 154 - 159). (IFAC Papers OnLine; Vol. 51, No. 23). Groningen: IFAC-PapersOnLine. https://doi.org/10.1016/j.ifacol.2018.12.027
  12. Jia, J., Trentelman, H., Baar, W., & Camlibel, M. (2018). A sufficient condition for colored strong structural controllability of networks. In K. Camlibel, & H. Shim (Eds.), Proceedings of the 7th IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys18), August 27-28, Groningen, The Netherlands (pp. 16 - 21). (IFAC-PapersOnLine; Vol. 51, No. 23). Groningen: IFAC-PapersOnLine. https://doi.org/10.1016/j.ifacol.2018.12.004
  13. Leuenberger, G., & Wiering, M. A. (2018). Actor-critic reinforcement learning with neural networks in continuous games. In ICAART 2018 - Proceedings of the 10th International Conference on Agents and Artificial Intelligence (ICAART 2018 - Proceedings of the 10th International Conference on Agents and Artificial Intelligence; Vol. 2). SciTePress.
  14. Schiza, E. (2018). An e-health driven national healthcare ecosystem. [Groningen]: University of Groningen.
  15. Yang, C. (2018). Architectural assumptions and their management in software development. [Groningen]: Rijksuniversiteit Groningen.
  16. van Eemeren, F. H., & Verheij, B. (2018). Argumentation Theory in Formal and Computational Perspective. In P. Baroni, D. Gabbay, M. Giacomin, & L. van der Torre (Eds.), Handbook of Formal Argumentation (Vol. 1, pp. 3-73). College Publications.
  17. Alsahaf, A., Ducro, B., Veerkamp, R., Azzopardi, G., & Petkov, N. (2018). Assigning pigs to uniform target weight groups using machine learning: ProceedingsoftheWorldCongressonGeneticsAppliedtoLivestockProduction,11.112. In World Congress on Genetics Applied to Livestock Production (WCGALP) University of New Zealand.
  18. Baayen, R. H., van Rij, J., de Cat, C., & Wood, S. (2018). Autocorrelated errors in experimental data in the language sciences: Some solutions offered by Generalized Additive Mixed Models. In D. Speelman, K. Heylen, & D. Geeraerts (Eds.), Mixed-Effects Regression Models in Linguistics (pp. 49-69). (Quantitative Methods in the Humanities and Social Sciences). Springer International Publishing AG. https://doi.org/10.1007/978-3-319-69830-4
  19. Buhagiar, J., Strisciuglio, N., Petkov, N., & Azzopardi, G. (2018). Automatic Segmentation of Indoor and Outdoor Scenes from Visual Lifelogging. Paper presented at Applications of Intelligent Systems 2018, Las Palmas de Gran Canaria, Spain.
  20. Strisciuglio, N., Azzopardi, G., & Petkov, N. (2018). Brain-inspired robust delineation operator. In European Conference of Computer Vision (ECCV) 2018: Workshop on Brain-inspired computer vision
  21. Verbree, R., van Rij, J., & Sprenger, S. (2018). Cognitve Effort in Speech Production: Insights from Pupillometry during Fluent and Stuttered Speech. Poster session presented at TABU Dag 2018, Groningen, Netherlands.
  22. Pieters, M., & Wiering, M. (2018). Comparison of machine learning techniques for multi-label genre classification. In B. Verheij, & M. Wiering (Eds.), Arti fi cial Intelligence: 29th Benelux Conference, BNAIC 2017 Groningen, The Netherlands, November 8 – 9, 2017 Revised Selected Papers (pp. 131-145). ( Communications in Computer and Information Science ; Vol. 823). Cham: Springer International Publishing AG. https://doi.org/10.1007/978-3-319-76892-2_10
  23. Silvis, M. H., & Verstappen, R. W. C. P. (2018). Constructing Physically Consistent Subgrid-Scale Models for Large-Eddy Simulation of Incompressible Turbulent Flows. In M. O. D., V. Couaillier, J-L. Estivalezes, V. Gleize, & T. HiêpLê (Eds.), Turbulence and Interactions: Proceedings of the TI 2015 Conference, June 11-14, 2015, Cargèse, Corsica, France (pp. 241-247). (Notes on Numerical Fluid Mechanics and Multidisciplinary Design; Vol. 135). Cham: Springer. https://doi.org/10.1007/978-3-319-60387-2_26
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