Publications
Fundamental AI
- Jackson, J., Laurenti, L., Frew, E., & Lahijanian, M. (2021). Synergistic Offline-Online Control Synthesis via Local Gaussian Process Regression. IEEE Conference on Decision and Control (CDC)
- Jackson, J., Laurenti, L., Frew, E., & Lahijanian, M. (2021, May). Strategy synthesis for partially-known switched stochastic systems. International Conference on Hybrid Systems: Computation and Control (pp. 1-11).
- Delimpaltadakis, G., Laurenti, L., & Mazo Jr, M. (2021). Abstracting the sampling behaviour of stochastic linear periodic event-triggered control systems. IEEE Conference on Decision and Control (CDC)
- Wicker, M., Laurenti, L., Patane, A., Paoletti, N., Abate, A., & Kwiatkowska, M. (2021). Certification of iterative predictions in Bayesian neural networks. In Uncertainty in Artificial Intelligence (pp. 1713-1723). PMLR.
- Siebert, L. C., Lupetti, M. L., Aizenberg, E., Beckers, N., Zgonnikov, A., Veluwenkamp, H., Abbink, D., Giaccardi, E., Houben, G.-J., Jonker, C. M., Hoven, J. van den, Forster, D., & Lagendijk, R. L. (2021). Meaningful human control over AI systems: Beyond talking the talk. http://arxiv.org/abs/2112.01298
- Peschl, M., Zgonnikov, A., Oliehoek, F. A., & Siebert, L. C. (2021). MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active Learning. http://arxiv.org/abs/2201.00012
Applied AI
- Alessandro Tognan, Luca Laurenti, & Enrico Salvati. (2022). Contour Method with Uncertainty Quantification: A Robust And Optimised Framework via Gaussian Process Regression. Experimental Mechanics
- Cardelli, L., Kwiatkowska, M., & Laurenti, L. (2021). A Language for Modeling and Optimizing Experimental Biological Protocols. Computation, 9(10), 107.
- Siebinga, O., Zgonnikov, A., & Abbink, D. (2021). Validating human driver models for interaction-aware automated vehicle controllers: A human factors approach. http://arxiv.org/abs/2109.13077
- Zgonnikov, A., Abbink, D., & Markkula, G. (2020). Should I stay or should I go? Evidence accumulation drives decision making in human drivers. https://doi.org/10.31234/osf.io/p8dxn
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