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	Quantification of MR spectra by deep learning in an idealized setting: investigation of forms of input, network architectures, optimization by ensembles of networks, and training bias Rizzo, R., Dziadosz, M., Kyathanahally, S. P., Shamaei, A., & Kreis, R. (2023). Quantification of MR spectra by deep learning in an idealized setting: investigation of forms of input, network architectures, optimization by ensembles of networks, and training bias. Magnetic Resonance in Medicine, 89(5), 1707-1727. https://doi.org/10.1002/mrm.29561 Detailed Record Published Version
	Reliability of quantification estimates in MR spectroscopy: CNNs vs traditional model fitting Rizzo, R., Dziadosz, M., Kyathanahally, S. P., Reyes, M., & Kreis, R. (2022). Reliability of quantification estimates in MR spectroscopy: CNNs vs traditional model fitting. In L. Wang, Q. Dou, P. T. Fletcher, S. Speidel, & S. Li (Eds.), Lecture notes in computer science: Vol. 13438. Medical image computing and computer assisted intervention - MICCAI 2022. 25th international conference, Singapore, September 18-22, 2022, proceedings, part VIII (pp. 715-724). https://doi.org/10.1007/978-3-031-16452-1_68 Detailed Record Published Version
	Early bursts of body size and shape evolution are rare in comparative data Harmon, L. J., Losos, J. B., Davies, T. J., Gillespie, R. G., Gittleman, J. L., Jennings, W. B., … Mooers, A. Ø. (2010). Early bursts of body size and shape evolution are rare in comparative data. Evolution, International Journal of Organic Evolution, 64(8), 2385-2396. https://doi.org/10.1111/j.1558-5646.2010.01025.x Detailed Record Published Version