Does preprocessing help under congestion?
K.-T. Foerster, J. Korhonen, J. Rybicki, S. Schmid, in:, Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing, ACM, 2019, pp. 259–261.

Autoregulation of bacterial gene expression: lessons from the MazEF toxin–antitoxin system
N. Nikolic, Current Genetics 65 (2019) 133–138.

Bi-Sobolev solutions to the prescribed Jacobian inequality in the plane with L p data and applications to nonlinear elasticity
J.L. Fischer, O. Kneuss, Journal of Differential Equations 266 (2019) 257–311.

Epigenetic cues modulating the generation of cell type diversity in the cerebral cortex
N. Amberg, S. Laukoter, S. Hippenmeyer, Journal of Neurochemistry 149 (2019) 12–26.

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

Harmonic dynamics of the Abelian sandpile
M. Lang, M. Shkolnikov, Proceedings of the National Academy of Sciences 116 (2019) 2821–2830.

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

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

On the fairness of disentangled representations
F. Locatello, G. Abbati, T. Rainforth, S. Bauer, B. Schölkopf, O. Bachem, in:, Advances in Neural Information Processing Systems, 2019, pp. 14611–14624.

Stochastic Frank-Wolfe for composite convex minimization
F. Locatello, A. Yurtsever, O. Fercoq, V. Cevher, in:, Advances in Neural Information Processing Systems, 2019, pp. 14291–14301.

Are disentangled representations helpful for abstract visual reasoning?
S. van Steenkiste, F. Locatello, J. Schmidhuber, O. Bachem, in:, Advances in Neural Information Processing Systems, 2019.

Challenging common assumptions in the unsupervised learning of disentangled representations
F. Locatello, S. Bauer, M. Lucic, G. Rätsch, S. Gelly, B. Schölkopf, O. Bachem, in:, Proceedings of the 36th International Conference on Machine Learning, ML Research Press, 2019, pp. 4114–4124.

Limiting shapes of confined lipid vesicles
B. Kavcic, A. Sakashita, H. Noguchi, P. Ziherl, Soft Matter 15 (2019) 602–614.

On the geometry of geodesics in discrete optimal transport
M. Erbar, J. Maas, M. Wirth, Calculus of Variations and Partial Differential Equations 58 (2019).

On the transfer of inductive bias from simulation to the real world: a new disentanglement dataset
M.W. Gondal, M. Wüthrich, . Miladinovi, F. Locatello, M. Breidt, V. Volchkov, J. Akpo, O. Bachem, B. Schölkopf, S. Bauer, in:, Advances in Neural Information Processing Systems, 2019.

Recognizing weak embeddings of graphs
H. Akitaya, R. Fulek, C. Tóth, ACM Transactions on Algorithms 15 (2019).

Automatic time-unbounded reachability analysis of hybrid systems
M. Giacobbe, Automatic Time-Unbounded Reachability Analysis of Hybrid Systems, Institute of Science and Technology Austria, 2019.

Data from: The consequences of an introgression event
N.H. Barton, (2019).

The Repo homeodomain transcription factor suppresses hematopoiesis in Drosophila and preserves the glial fate
G. Trébuchet, P.B. Cattenoz, J. Zsámboki, D. Mazaud, D.E. Siekhaus, M. Fanto, A. Giangrande, Journal of Neuroscience 39 (2019) 238–255.

The wonderful compactification for quantum groups
I.V. Ganev, Journal of the London Mathematical Society 99 (2019) 778–806.