N. Petridou, S. Grigolon, G. Salbreux, E. B. Hannezo, and C.-P. J. Heisenberg, “Fluidization-mediated tissue spreading by mitotic cell rounding and non-canonical Wnt signalling,” Nature Cell Biology, vol. 21. Nature Publishing Group, pp. 169–178, 2019.

M. Lang and M. Shkolnikov, “Harmonic dynamics of the Abelian sandpile,” Proceedings of the National Academy of Sciences, vol. 116, no. 8. National Academy of Sciences, pp. 2821–2830, 2019.

F. Locatello, M. Tschannen, S. Bauer, G. Rätsch, B. Schölkopf, and O. Bachem, “Disentangling factors of variation using few labels,” in 8th International Conference on Learning Representations, Virtual, 2019.

L. Gresele, P. K. Rubenstein, A. Mehrjou, F. Locatello, and B. Schölkopf, “The incomplete Rosetta Stone problem: Identifiability results for multi-view nonlinear ICA,” in Proceedings of the 35th Conference on Uncertainty in Artificial  Intelligence, Tel Aviv, Israel, 2019, vol. 115, pp. 217–227.

F. Locatello, G. Abbati, T. Rainforth, S. Bauer, B. Schölkopf, and O. Bachem, “On the fairness of disentangled representations,” in Advances in Neural Information Processing Systems, Vancouver, Canada, 2019, vol. 32, pp. 14611–14624.

F. Locatello, A. Yurtsever, O. Fercoq, and V. Cevher, “Stochastic Frank-Wolfe for composite convex minimization,” in Advances in Neural Information Processing Systems, Vancouver, Canada, 2019, vol. 32, pp. 14291–14301.

S. van Steenkiste, F. Locatello, J. Schmidhuber, and O. Bachem, “Are disentangled representations helpful for abstract visual reasoning?,” in Advances in Neural Information Processing Systems, Vancouver, Canada, 2019, vol. 32.

F. Locatello et al., “Challenging common assumptions in the unsupervised learning of disentangled representations,” in Proceedings of the 36th International Conference on Machine Learning, Long Beach, CA, United States, 2019, vol. 97, pp. 4114–4124.

B. Kavcic, A. Sakashita, H. Noguchi, and P. Ziherl, “Limiting shapes of confined lipid vesicles,” Soft Matter, vol. 15, no. 4. Royal Society of Chemistry, pp. 602–614, 2019.

M. Erbar, J. Maas, and M. Wirth, “On the geometry of geodesics in discrete optimal transport,” Calculus of Variations and Partial Differential Equations, vol. 58, no. 1. Springer, 2019.

M. W. Gondal et al., “On the transfer of inductive bias from simulation to the real world: a new disentanglement dataset,” in Advances in Neural Information Processing Systems, Vancouver, Canada, 2019, vol. 32.

H. Akitaya, R. Fulek, and C. Tóth, “Recognizing weak embeddings of graphs,” ACM Transactions on Algorithms, vol. 15, no. 4. ACM, 2019.

M. Giacobbe, “Automatic time-unbounded reachability analysis of hybrid systems,” Institute of Science and Technology Austria, 2019.

N. H. Barton, “Data from: The consequences of an introgression event.” Dryad, 2019.

G. Trébuchet et al., “The Repo homeodomain transcription factor suppresses hematopoiesis in Drosophila and preserves the glial fate,” Journal of Neuroscience, vol. 39, no. 2. Society for Neuroscience, pp. 238–255, 2019.

I. V. Ganev, “The wonderful compactification for quantum groups,” Journal of the London Mathematical Society, vol. 99, no. 3. Wiley, pp. 778–806, 2019.

M. K. Vasileva, “Molecular mechanisms of endomembrane trafficking in Arabidopsis thaliana,” Institute of Science and Technology Austria, 2019.

S. A. Cepeda Humerez, “Estimating information flow in single cells,” Institute of Science and Technology Austria, 2019.

R. Prizak, “Coevolution of transcription factors and their binding sites in sequence space,” Institute of Science and Technology Austria, 2019.

T. K. Srivastava, “On derived equivalences of k3 surfaces in positive characteristic,” Documenta Mathematica, vol. 24. EMS Press, pp. 1135–1177, 2019.