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	Data assimilation of in situ and satellite remote sensing data to 3D hydrodynamic lake models: a case study using Delft3D-FLOW v4.03 and OpenDA v2.4 Baracchini, T., Chu, P. Y., Šukys, J., Lieberherr, G., Wunderle, S., Wüest, A., & Bouffard, D. (2020). Data assimilation of in situ and satellite remote sensing data to 3D hydrodynamic lake models: a case study using Delft3D-FLOW v4.03 and OpenDA v2.4. Geoscientific Model Development, 13(3), 1267-1284. https://doi.org/10.5194/gmd-13-1267-2020 Detailed Record Published Version
	Multilevel control variates for uncertainty quantification in simulations of cloud cavitation Šukys, J., Rasthofer, U., Wermelinger, F., Hadjidoukas, P., & Koumoutsakos, P. (2018). Multilevel control variates for uncertainty quantification in simulations of cloud cavitation. SIAM Journal on Scientific Computing, 40(5), B1361-B1390. https://doi.org/10.1137/17M1129684 Detailed Record Published Version
	SPUX: scalable particle Markov Chain Monte Carlo for uncertainty quantification in stochastic ecological models Šukys, J., & Kattwinkel, M. (2018). SPUX: scalable particle Markov Chain Monte Carlo for uncertainty quantification in stochastic ecological models. In S. Bassini, M. Danelutto, P. Dazzi, G. R. Joubert, & F. Peters (Eds.), Advances in parallel computing: Vol. 32. Parallel computing is everywhere (pp. 159-168). https://doi.org/10.3233/978-1-61499-843-3-159 Detailed Record Accepted Version