Rannen-Triki, A., Berman, M., Kolmogorov, V., &; Blaschko, M. B. (2019). Function norms for neural networks. In Proceedings of the 2019 International Conference on Computer Vision Workshop. Seoul, South Korea: IEEE.https://doi.org/10.1109/ICCVW.2019.00097 

Barton, N. H., &; Etheridge, A. (2019). Mathematical models in population genetics. In D. Balding, I. Moltke, &; J. Marioni (Eds.), Handbook of statistical genomics (4th ed., pp. 115–144). Wiley.https://doi.org/10.1002/9781119487845.ch4 

Avvakumov, S., Karasev, R., &; Skopenkov, A. (n.d.). Stronger counterexamples to the topological Tverberg conjecture. arXiv. arXiv.

Fuchsbauer, G., Kamath Hosdurg, C., Klein, K., &; Pietrzak, K. Z. (2019). Adaptively secure proxy re-encryption (Vol. 11443, pp. 317–346). Presented at the PKC: Public-Key Cryptograhy, Beijing, China: Springer Nature.https://doi.org/10.1007/978-3-030-17259-6_11 

Mayzel, J., Steinberg, V., &; Varshney, A. (2019). Stokes flow analogous to viscous electron current in graphene. Nature Communications. Springer Nature.https://doi.org/10.1038/s41467-019-08916-5 

Varshney, A., &; Steinberg, V. (2019). Elastic alfven waves in elastic turbulence. Nature Communications. Springer Nature.https://doi.org/10.1038/s41467-019-08551-0 

Amberg, N., Sotiropoulou, P. A., Heller, G., Lichtenberger, B. M., Holcmann, M., Camurdanoglu, B.,https://doi.org/10.1016/j.isci.2019.04.018__Sibilia, M. (2019). EGFR controls hair shaft differentiation in a -independent manner. IScience. Elsevier.https://doi.org/10.1016/j.isci.2019.04.018 

Dietlein, A. M., Gebert, M., &; Müller, P. (2019). Perturbations of continuum random Schrödinger operators with applications to Anderson orthogonality and the spectral shift function. Journal of Spectral Theory. European Mathematical Society Publishing House.https://doi.org/10.4171/jst/267 

Flandoli, F., Priola, E., &; Zanco, G. A. (2019). A mean-field model with discontinuous coefficients for neurons with spatial interaction. Discrete and Continuous Dynamical Systems. American Institute of Mathematical Sciences.https://doi.org/10.3934/dcds.2019126 

Foerster, K.-T., Korhonen, J., Rybicki, J., &; Schmid, S. (2019). Does preprocessing help under congestion? In Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing (pp. 259–261). Toronto, ON, Canada: ACM.https://doi.org/10.1145/3293611.3331581 

Nikolic, N. (2019). Autoregulation of bacterial gene expression: lessons from the MazEF toxin–antitoxin system. Current Genetics. Springer.https://doi.org/10.1007/s00294-018-0879-8 

Fischer, J. L., &; Kneuss, O. (2019). Bi-Sobolev solutions to the prescribed Jacobian inequality in the plane with L p data and applications to nonlinear elasticity. Journal of Differential Equations. Elsevier.https://doi.org/10.1016/j.jde.2018.07.045 

Amberg, N., Laukoter, S., &; Hippenmeyer, S. (2019). Epigenetic cues modulating the generation of cell type diversity in the cerebral cortex. Journal of Neurochemistry. Wiley.https://doi.org/10.1111/jnc.14601 

Petridou, N., Grigolon, S., Salbreux, G., Hannezo, E. B., &; Heisenberg, C.-P. J. (2019). Fluidization-mediated tissue spreading by mitotic cell rounding and non-canonical Wnt signalling. Nature Cell Biology. Nature Publishing Group.https://doi.org/10.1038/s41556-018-0247-4 

Lang, M., &; Shkolnikov, M. (2019). Harmonic dynamics of the Abelian sandpile. Proceedings of the National Academy of Sciences. National Academy of Sciences.https://doi.org/10.1073/pnas.1812015116 

Locatello, F., Tschannen, M., Bauer, S., Rätsch, G., Schölkopf, B., &; Bachem, O. (2019). Disentangling factors of variation using few labels. In 8th International Conference on Learning Representations. Virtual.

Gresele, L., Rubenstein, P. K., Mehrjou, A., Locatello, F., &; Schölkopf, B. (2019). The incomplete Rosetta Stone problem: Identifiability results for multi-view nonlinear ICA. In Proceedings of the 35th Conference on Uncertainty in Artificial  Intelligence (Vol. 115, pp. 217–227). Tel Aviv, Israel: ML Research Press.

Locatello, F., Abbati, G., Rainforth, T., Bauer, S., Schölkopf, B., &; Bachem, O. (2019). On the fairness of disentangled representations. In Advances in Neural Information Processing Systems (Vol. 32, pp. 14611–14624). Vancouver, Canada.

Locatello, F., Yurtsever, A., Fercoq, O., &; Cevher, V. (2019). Stochastic Frank-Wolfe for composite convex minimization. In Advances in Neural Information Processing Systems (Vol. 32, pp. 14291–14301). Vancouver, Canada.

Steenkiste, S. van, Locatello, F., Schmidhuber, J., &; Bachem, O. (2019). Are disentangled representations helpful for abstract visual reasoning? In Advances in Neural Information Processing Systems (Vol. 32). Vancouver, Canada.

Locatello, F., Bauer, S., Lucic, M., Rätsch, G., Gelly, S., Schölkopf, B., &; Bachem, O. (2019). Challenging common assumptions in the unsupervised learning of disentangled representations. In Proceedings of the 36th International Conference on Machine Learning (Vol. 97, pp. 4114–4124). Long Beach, CA, United States: ML Research Press.

Kavcic, B., Sakashita, A., Noguchi, H., &; Ziherl, P. (2019). Limiting shapes of confined lipid vesicles. Soft Matter. Royal Society of Chemistry.https://doi.org/10.1039/c8sm01956h 

Erbar, M., Maas, J., &; Wirth, M. (2019). On the geometry of geodesics in discrete optimal transport. Calculus of Variations and Partial Differential Equations. Springer.https://doi.org/10.1007/s00526-018-1456-1 

Gondal, M. W., Wüthrich, M., Miladinovi, ., Locatello, F., Breidt, M., Volchkov, V.,  Bauer, S. (2019). On the transfer of inductive bias from simulation to the real world: a new disentanglement dataset. In Advances in Neural Information Processing Systems (Vol. 32). Vancouver, Canada.

Akitaya, H., Fulek, R., &; Tóth, C. (2019). Recognizing weak embeddings of graphs. ACM Transactions on Algorithms. ACM.https://doi.org/10.1145/3344549 

Giacobbe, M. (2019). Automatic time-unbounded reachability analysis of hybrid systems. Institute of Science and Technology Austria.https://doi.org/10.15479/AT:ISTA:6894 

Barton, N. H. (2019). Data from: The consequences of an introgression event. Dryad.https://doi.org/10.5061/dryad.2kb6fh4 

Trébuchet, G., Cattenoz, P. B., Zsámboki, J., Mazaud, D., Siekhaus, D. E., Fanto, M., &; Giangrande, A. (2019). The Repo homeodomain transcription factor suppresses hematopoiesis in Drosophila and preserves the glial fate. Journal of Neuroscience. Society for Neuroscience.https://doi.org/10.1523/JNEUROSCI.1059-18.2018 

Ganev, I. V. (2019). The wonderful compactification for quantum groups. Journal of the London Mathematical Society. Wiley.https://doi.org/10.1112/jlms.12193 

Vasileva, M. K. (2019). Molecular mechanisms of endomembrane trafficking in Arabidopsis thaliana. Institute of Science and Technology Austria.https://doi.org/10.15479/AT:ISTA:7172 

Goudarzi, M., Boquet-Pujadas, A., Olivo-Marin, J. C., &; Raz, E. (2019). Fluid dynamics during bleb formation in migrating cells in vivo. PLOS ONE. Public Library of Science.https://doi.org/10.1371/journal.pone.0212699 

Cepeda Humerez, S. A. (2019). Estimating information flow in single cells. Institute of Science and Technology Austria.https://doi.org/10.15479/AT:ISTA:6473 

Prizak, R. (2019). Coevolution of transcription factors and their binding sites in sequence space. Institute of Science and Technology Austria.https://doi.org/10.15479/at:ista:th6071 

Srivastava, T. K. (2019). On derived equivalences of k3 surfaces in positive characteristic. Documenta Mathematica. EMS Press.https://doi.org/10.25537/dm.2019v24.1135-1177 

Ferrari, P., Ghosal, P., &; Nejjar, P. (2019). Limit law of a second class particle in TASEP with non-random initial condition. Annales de l’institut Henri Poincare (B) Probability and Statistics. Institute of Mathematical Statistics.https://doi.org/10.1214/18-AIHP916 

Danowski, P. (2019). An Austrian proposal for the classification of Open Access Tuples (COAT) - distinguish different open access types beyond colors. Mitteilungen Der Vereinigung Österreichischer Bibliothekarinnen Und Bibliothekare. Vereinigung Österreichischer Bibliothekarinnen und Bibliothekare.https://doi.org/10.31263/voebm.v72i1.2276 

Khatoniar, M., Yama, N., Ghazaryan, A., Guddala, S., Ghaemi, P., &; Menon, V. (2019). Room temperature control of valley coherence in bilayer W exciton polaritons. In CLEO: Applications and Technology. San Jose, CA, United States: Optica  Publishing Group.https://doi.org/10.1364/cleo_at.2019.jtu2a.52 

Rueda Sanchez, A. R., Sedlmeir, F., Leuchs, G., Kumari, M., &; Schwefel, H. G. L. (2019). Resonant electro-optic frequency comb generation in lithium niobate disk resonator inside a microwave cavity. In Nonlinear Optics, OSA Technical Digest. Waikoloa Beach, Hawaii (HI), United States: Optica  Publishing Group.https://doi.org/10.1364/NLO.2019.NM2A.5 

Alt, J., Erdös, L., Krüger, T. H., &; Nemish, Y. (2019). Location of the spectrum of Kronecker random matrices. Annales de l’institut Henri Poincare. Institut Henri Poincaré.https://doi.org/10.1214/18-AIHP894 

Andergassen, D., Muckenhuber, M., Bammer, P. C., Kulinski, T. M., Theussl, H.-C., Shimizu, T.,https://doi.org/10.1371/journal.pgen.1008268__Hudson, Q. J. (2019). The Airn lncRNA does not require any DNA elements within its locus to silence distant imprinted genes. PLoS Genetics. Public Library of Science.https://doi.org/10.1371/journal.pgen.1008268 

Wang, J. W. J. L., Lombardi, F., Zhang, X., Anaclet, C., &; Ivanov, P. C. (2019). Non-equilibrium critical dynamics of bursts in ;8 and ;4 rhythms as fundamental characteristic of sleep and wake micro-architecture. PLoS Computational Biology. Public Library of Science.https://doi.org/10.1371/journal.pcbi.1007268 

Phuong, M., &; Lampert, C. (2019). Towards understanding knowledge distillation. In Proceedings of the 36th International Conference on Machine Learning (Vol. 97, pp. 5142–5151). Long Beach, CA, United States: ML Research Press.

Konstantinov, N. H., &; Lampert, C. (2019). Robust learning from untrusted sources. In Proceedings of the 36th International Conference on Machine Learning (Vol. 97, pp. 3488–3498). Long Beach, CA, USA: ML Research Press.

Huang, D., Sun, Y., Ma, Z., Ke, M., Cui, Y., Chen, Z.,https://doi.org/10.1073/pnas.1911892116__Chen, X. (2019). Salicylic acid-mediated plasmodesmal closure via Remorin-dependent lipid organization. Proceedings of the National Academy of Sciences of the United States of America. Proceedings of the National Academy of Sciences.https://doi.org/10.1073/pnas.1911892116 

Wright, A. E., Darolti, I., Bloch, N. I., Oostra, V., Sandkam, B. A., Buechel, S. D.,https://doi.org/10.1073/pnas.1905555116__Mank, J. E. (2019). On the power to detect rare recombination events. Proceedings of the National Academy of Sciences of the United States of America. Proceedings of the National Academy of Sciences.https://doi.org/10.1073/pnas.1905555116 

Pickup, M., Barton, N. H., Brandvain, Y., Fraisse, C., Yakimowski, S., Dixit, T.,https://doi.org/10.1111/nph.16180__Field, D. (2019). Mating system variation in hybrid zones: Facilitation, barriers and asymmetries to gene flow. New Phytologist. Wiley.https://doi.org/10.1111/nph.16180 

Fulek, R., Gärtner, B., Kupavskii, A., Valtr, P., &; Wagner, U. (2019). The crossing Tverberg theorem. In 35th International Symposium on Computational Geometry (Vol. 129, p. 38:1-38:13). Portland, OR, United States: Schloss Dagstuhl - Leibniz-Zentrum für Informatik.https://doi.org/10.4230/LIPICS.SOCG.2019.38 

Alistarh, D.-A., Aspnes, J., Ellen, F., Gelashvili, R., &; Zhu, L. (2019). Why extension-based proofs fail. In Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing (pp. 986–996). Phoenix, AZ, United States: ACM Press.https://doi.org/10.1145/3313276.3316407 

Biniaz, A., Jain, K., Lubiw, A., Masárová, Z., Miltzow, T., Mondal, D.,  Turcotte, A. (n.d.). Token swapping on trees. arXiv.

Huylmans, A. K., Toups, M. A., Macon, A., Gammerdinger, W. J., &; Vicoso, B. (2019). Sex-biased gene expression and dosage compensation on the Artemia franciscana Z-chromosome. Genome Biology and Evolution. Oxford University Press.https://doi.org/10.1093/gbe/evz053