Kutzer, M., Kurtz, J., &; Armitage, S. (2018). Genotype and diet affect resistance, survival, and fecundity but not fecundity tolerance. Journal of Evolutionary Biology. Wiley.https://doi.org/10.1111/jeb.13211 

Tarlungeanu, D.-C., &; Novarino, G. (2018). Genomics in neurodevelopmental disorders: an avenue to personalized medicine. Experimental &; Molecular Medicine. Springer Nature.https://doi.org/10.1038/s12276-018-0129-7 

Lundholm, D., &; Seiringer, R. (2018). Fermionic behavior of ideal anyons. Letters in Mathematical Physics. Springer.https://doi.org/10.1007/s11005-018-1091-y 

Richter, R., Baranova, N. S., Day, A., &; Kwok, J. (2018). Glycosaminoglycans in extracellular matrix organisation: Are concepts from soft matter physics key to understanding the formation of perineuronal nets? Current Opinion in Structural Biology. Elsevier.https://doi.org/10.1016/j.sbi.2017.12.002 

Harrison, M., Jongepier, E., Robertson, H., Arning, N., Bitard Feildel, T., Chao, H.,https://doi.org/10.1038/s41559-017-0459-1__Bornberg Bauer, E. (2018). Hemimetabolous genomes reveal molecular basis of termite eusociality. Nature Ecology and Evolution. Springer Nature.https://doi.org/10.1038/s41559-017-0459-1 

Oliveto, P., Paixao, T., Pérez Heredia, J., Sudholt, D., &; Trubenova, B. (2018). How to escape local optima in black box optimisation when non elitism outperforms elitism. Algorithmica. Springer.https://doi.org/10.1007/s00453-017-0369-2 

Darrell, T., Lampert, C., Sebe, N., Wu, Y., &; Yan, Y. (2018). Guest editors’ introduction to the special section on learning with Shared information for computer vision and multimedia analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE.https://doi.org/10.1109/TPAMI.2018.2804998 

Harrison, M. C., Jongepier, E., Robertson, H. M., Arning, N., Bitard-Feildel, T., Chao, H.,https://doi.org/10.5061/dryad.51d4r__Bornberg-Bauer, E. (2018). Data from: Hemimetabolous genomes reveal molecular basis of termite eusociality. Dryad.https://doi.org/10.5061/dryad.51d4r 

Arbel Raviv, M., &; Brown, T. A. (2018). Harnessing epoch-based reclamation for efficient range queries (Vol. 53, pp. 14–27). Presented at the PPoPP: Principles and Practice of Parallel Programming, Vienna, Austria: ACM.https://doi.org/10.1145/3178487.3178489 

Chen, T., Kula, B., Nagy, B., Barzan, R., Gall, A., Ehrlich, I., &; Kukley, M. (2018). In Vivo regulation of Oligodendrocyte processor cell proliferation and differentiation by the AMPA-receptor Subunit Glu. Cell Reports. Elsevier.https://doi.org/10.1016/j.celrep.2018.09.066 

Reversat, A., &; Sixt, M. K. (2018). IgM’s exit route. Journal of Experimental Medicine. Rockefeller University Press.https://doi.org/10.1084/jem.20181934 

Dodier, P., Frischer, J., Wang, W., Auzinger, T., Mallouhi, A., Serles, W.,https://doi.org/10.1016/j.wneu.2018.02.096__Bavinzski, G. (2018). Immediate flow disruption as a prognostic factor after flow diverter treatment long term experience with the pipeline embolization device. World Neurosurgery. Elsevier.https://doi.org/10.1016/j.wneu.2018.02.096 

Akopyan, A., &; Bobenko, A. (2018). Incircular nets and confocal conics. Transactions of the American Mathematical Society. American Mathematical Society.https://doi.org/10.1090/tran/7292 

Metzler, S., Schrempf, A., &; Heinze, J. (2018). Individual- and ejaculate-specific sperm traits in ant males. Journal of Insect Physiology. Elsevier.https://doi.org/10.1016/j.jinsphys.2017.12.003 

Avni, G., Henzinger, T. A., &; Ibsen-Jensen, R. (2018). Infinite-duration poorman-bidding games (Vol. 11316, pp. 21–36). Presented at the 14th International Conference on Web and Internet Economics, WINE, Oxford, UK: Springer.https://doi.org/10.1007/978-3-030-04612-5_2 

Dick, R., Zadrozny, K. K., Xu, C., Schur, F. K., Lyddon, T. D., Ricana, C. L.,https://doi.org/10.1038/s41586-018-0396-4__Vogt, V. (2018). Inositol phosphates are assembly co-factors for HIV-1. Nature. Nature Publishing Group.https://doi.org/10.1038/s41586-018-0396-4 

Kalinin, N., &; Shkolnikov, M. (2018). Introduction to tropical series and wave dynamic on them. Discrete and Continuous Dynamical Systems- Series A. AIMS.https://doi.org/10.3934/dcds.2018120 

Locatello, F., Dresdner, G., Khanna, R., Valera, I., &; Rätsch, G. (2018). Boosting black box variational inference. In Advances in Neural Information Processing Systems (Vol. 31). Montreal, Canada: Neural Information Processing Systems Foundation.

Locatello, F., Khanna, R., Ghosh, J., &; Rätsch, G. (2018). Boosting variational inference: An optimization perspective. In Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (Vol. 84, pp. 464–472). Playa Blanca, Lanzarote: ML Research Press.

Fortuin, V., Hüser, M., Locatello, F., Strathmann, H., &; Rätsch, G. (2018). SOM-VAE: Interpretable discrete representation learning on time series. In International Conference on Learning Representations. New Orleans, LA, United States.