Mazur, E., Kurczyñska, E., &; Friml, J. (2014). Cellular events during interfascicular cambium ontogenesis in inflorescence stems of Arabidopsis. Protoplasma. Springer.https://doi.org/10.1007/s00709-014-0620-5 

Rubio, M., Fukazawa, Y., Kamasawa, N., Clarkson, C., Molnár, E., &; Shigemoto, R. (2014). Target- and input-dependent organization of AMPA and NMDA receptors in synaptic connections of the cochlear nucleus. Journal of Comparative Neurology. Wiley-Blackwell.https://doi.org/10.1002/cne.23654 

Skouras, M., Thomaszewski, B., Kaufmann, P., Garg, A., Bickel, B., Grinspun, E., &; Gross, M. (2014). Designing inflatable structures (Vol. 33). Presented at the SIGGRAPH: Special Interest Group on Computer Graphics and Interactive Techniques, ACM.https://doi.org/10.1145/2601097.2601166 

BacHer, M., Whiting, E., Bickel, B., &; Sorkine Hornung, O. (2014). Spin-It: Optimizing moment of inertia for spinnable objects (Vol. 33). Presented at the SIGGRAPH: 41st International Conference and Exhibition on Computer Graphics and Interactive Techniques, ACM.https://doi.org/10.1145/2601097.2601157 

Bermano, A., Bradley, D., Beeler, T., Zund, F., Nowrouzezahrai, D., Baran, I.,https://doi.org/10.1145/2546276__Groß, M. (2014). Facial performance enhancement using dynamic shape space analysis. ACM Transactions on Graphics. ACM.https://doi.org/10.1145/2546276 

Carlen, E., &; Maas, J. (2014). An analog of the 2-Wasserstein metric in non-commutative probability under which the fermionic Fokker-Planck equation is gradient flow for the entropy. Communications in Mathematical Physics. Springer.https://doi.org/10.1007/s00220-014-2124-8 

Hairer, M., Maas, J., &; Weber, H. (2014). Approximating Rough Stochastic PDEs. Communications on Pure and Applied Mathematics. Wiley-Blackwell.https://doi.org/10.1002/cpa.21495 

Erbar, M., &; Maas, J. (2014). Gradient flow structures for discrete porous medium equations. Discrete and Continuous Dynamical Systems- Series A. Southwest Missouri State University.https://doi.org/10.3934/dcds.2014.34.1355Â   

Otterbach, J., &; Lemeshko, M. (2014). Dissipative preparation of spatial order in Rydberg-dressed Bose-Einstein condensates. Physical Review Letters. American Physical Society.https://doi.org/10.1103/PhysRevLett.113.070401 

Bauer, U., &; Lesnick, M. (2014). Induced matchings of barcodes and the algebraic stability of persistence. In Proceedings of the Annual Symposium on Computational Geometry (pp. 355–364). Kyoto, Japan: ACM.https://doi.org/10.1145/2582112.2582168 

Matousek, J., &; Wagner, U. (2014). On Gromov’s method of selecting heavily covered points. Discrete &; Computational Geometry. Springer.https://doi.org/10.1007/s00454-014-9584-7 

Bauer, U., Ge, X., &; Wang, Y. (2014). Measuring distance between Reeb graphs. In Proceedings of the Annual Symposium on Computational Geometry (pp. 464–473). Kyoto, Japan: ACM.https://doi.org/10.1145/2582112.2582169 

Bauer, U., &; Edelsbrunner, H. (2014). The morse theory of cech and Delaunay filtrations. In Proceedings of the Annual Symposium on Computational Geometry (pp. 484–490). Kyoto, Japan: ACM.https://doi.org/10.1145/2582112.2582167 

Majumdar, R., Sixt, M. K., &; Parent, C. (2014). New paradigms in the establishment and maintenance of gradients during directed cell migration. Current Opinion in Cell Biology. Elsevier.https://doi.org/10.1016/j.ceb.2014.05.010 

Morvant, E. (2014). Domain Adaptation of Weighted Majority Votes via Perturbed Variation-Based Self-Labeling. Pattern Recognition Letters. Elsevier.https://doi.org/10.1016/j.patrec.2014.08.013 

Chai, X., Münzner, G., Zhao, S., Tinnes, S., Kowalski, J., Häussler, U.,https://doi.org/10.1093/cercor/bht067__Frotscher, M. (2014). Epilepsy-induced motility of differentiated neurons. Cerebral Cortex. Oxford University Press.https://doi.org/10.1093/cercor/bht067 

Kelleher, J., Etheridge, A., &; Barton, N. H. (2014). Coalescent simulation in continuous space: Algorithms for large neighbourhood size. Theoretical Population Biology. Academic Press.https://doi.org/10.1016/j.tpb.2014.05.001 

Barton, N. H., Novak, S., &; Paixao, T. (2014). Diverse forms of selection in evolution and computer science. PNAS. National Academy of Sciences.https://doi.org/10.1073/pnas.1410107111 

Kolesnikov, A., Guillaumin, M., Ferrari, V., &; Lampert, C. (2014). Closed-form approximate CRF training for scalable image segmentation. In D. Fleet, T. Pajdla, B. Schiele, &; T. Tuytelaars (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8691, pp. 550–565). Zurich, Switzerland: Springer.https://doi.org/10.1007/978-3-319-10578-9_36 

Khamis, S., &; Lampert, C. (2014). CoConut: Co-classification with output space regularization. In Proceedings of the British Machine Vision Conference 2014. Nottingham, UK: BMVA Press.