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Bombari, S., Amani, M. H., &; Mondelli, M. (2022). Memorization and optimization in deep neural networks with minimum over-parameterization. In 36th Conference on Neural Information Processing Systems (Vol. 35, pp. 7628–7640). Curran Associates.
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Zikelic, D., Lechner, M., Henzinger, T. A., &; Chatterjee, K. (n.d.). Learning control policies for stochastic systems with reach-avoid guarantees. arXiv.https://doi.org/10.48550/ARXIV.2210.05308 
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Norelli, A., Fumero, M., Maiorca, V., Moschella, L., Rodolà, E., &; Locatello, F. (n.d.). ASIF: Coupled data turns unimodal models to multimodal without training. arXiv.https://doi.org/10.48550/arXiv.2210.01738 
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Radler, P. (2022). In vitro reconstitution of Escherichia coli divisome activation. Institute of Science and Technology Austria.https://doi.org/10.15479/AT:ISTA:10934 
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Radler, P., Baranova, N. S., Dos Santos Caldas, P. R., Sommer, C. M., Lopez Pelegrin, M. D., Michalik, D., &; Loose, M. (2022). In vitro reconstitution of Escherichia coli divisome activation. Nature Communications. Springer Nature.https://doi.org/10.1038/s41467-022-30301-y 
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Schulz, R. (2022). Source Data (Chimeric GPCRs mimic distinct signaling pathways and modulate microglia responses). Institute of Science and Technology Austria.https://doi.org/10.15479/AT:ISTA:11542 
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Valentini, M., Borovkov, M., Prada, E., Martí-Sánchez, S., Botifoll, M., Hofmann, A. C.,https://doi.org/10.1038/s41586-022-05382-w__Katsaros, G. (2022). Majorana-like Coulomb spectroscopy in the absence of zero-bias peaks. Nature. Springer Nature.https://doi.org/10.1038/s41586-022-05382-w 
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Valentini, M., San-Jose, P., Arbiol, J., Marti-Sanchez, S., &; Botifoll, M. (2022). Data for “Majorana-like Coulomb spectroscopy in the absence of zero bias peaks.”https://doi.org/10.15479/AT:ISTA:12102__Institute of Science and Technology Austria.https://doi.org/10.15479/AT:ISTA:12102 
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Surendranadh, P., Arathoon, L. S., Baskett, C., Field, D., Pickup, M., &; Barton, N. H. (2022). Effects of fine-scale population structure on the distribution of heterozygosity in a long-term study of Antirrhinum majus. Genetics. Oxford University Press.https://doi.org/10.1093/genetics/iyac083 
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Surendranadh, P., Arathoon, L. S., Baskett, C., Field, D., Pickup, M., &; Barton, N. H. (2022). Effects of fine-scale population structure on the distribution of heterozygosity in a long-term study of Antirrhinum majus. Institute of Science and Technology Austria.https://doi.org/10.15479/at:ista:11321 
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Akopyan, A., &; Karasev, R. (2022). When different norms lead to same billiard trajectories? European Journal of Mathematics. Springer Nature.https://doi.org/10.1007/s40879-020-00405-0 
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Sperl, G. (2022). Homogenizing yarn simulations: Large-scale mechanics, small-scale detail, and quantitative fitting. Institute of Science and Technology Austria.https://doi.org/10.15479/at:ista:12103 
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Rzadkowski, W. (2022). Analytic and machine learning approaches to composite quantum impurities. Institute of Science and Technology Austria.https://doi.org/10.15479/at:ista:10759 
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Ingole, K. D., Nagarajan, N., Uhse, S., Giannini, C., &; Djamei, A. (2022). Tetracycline-controlled (TetON) gene expression system for the smut fungus Ustilago maydis. Frontiers in Fungal Biology. Frontiers Media.https://doi.org/10.3389/ffunb.2022.1029114 
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