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5967 Publications
2017 | Published | Conference Paper | IST-REx-ID: 989
Maas, J., Rumpf, M., & Simon, S. (2017). Transport based image morphing with intensity modulation. In F. Lauze, Y. Dong, & A. Bjorholm Dahl (Eds.) (Vol. 10302, pp. 563–577). Presented at the SSVM: Scale Space and Variational Methods in Computer Vision, Kolding, Denmark: Springer. https://doi.org/10.1007/978-3-319-58771-4_45
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2017 | Published | Journal Article | IST-REx-ID: 991
Chen, C., & Jonas, P. M. (2017). Synaptotagmins: That’s why so many. Neuron. Elsevier. https://doi.org/10.1016/j.neuron.2017.05.011
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2017 | Published | Journal Article | IST-REx-ID: 9445 |
Lyons, D. B., & Zilberman, D. (2017). DDM1 and Lsh remodelers allow methylation of DNA wrapped in nucleosomes. ELife. eLife Sciences Publications. https://doi.org/10.7554/elife.30674
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| PubMed | Europe PMC
2017 | Research Data | IST-REx-ID: 5568 |
Hahn, D. (2017). Source codes: Brittle fracture simulation with boundary elements for computer graphics. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:73
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2017 | Published | Thesis | IST-REx-ID: 992 |
Rolinek, M. (2017). Complexity of constraint satisfaction. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:th_815
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2017 | Published | Conference Paper | IST-REx-ID: 915 |
Swoboda, P., & Andres, B. (2017). A message passing algorithm for the minimum cost multicut problem (Vol. 2017, pp. 4990–4999). Presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States: IEEE. https://doi.org/10.1109/CVPR.2017.530
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2017 | Published | Conference Paper | IST-REx-ID: 916 |
Swoboda, P., Rother, C., Abu Alhaija, C., Kainmueller, D., & Savchynskyy, B. (2017). A study of lagrangean decompositions and dual ascent solvers for graph matching (Vol. 2017, pp. 7062–7071). Presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States: IEEE. https://doi.org/10.1109/CVPR.2017.747
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2017 | Published | Conference Paper | IST-REx-ID: 917 |
Swoboda, P., Kuske, J., & Savchynskyy, B. (2017). A dual ascent framework for Lagrangean decomposition of combinatorial problems (Vol. 2017, pp. 4950–4960). Presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States: IEEE. https://doi.org/10.1109/CVPR.2017.526
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2017 | Published | Conference Paper | IST-REx-ID: 274 |
Kolmogorov, V. (2017). A faster approximation algorithm for the Gibbs partition function. In Proceedings of the 31st Conference On Learning Theory (Vol. 75, pp. 228–249). ML Research Press.
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| arXiv
2017 | Published | Journal Article | IST-REx-ID: 1004 |
Ötvös, K., & Benková, E. (2017). Spatiotemporal mechanisms of root branching. Current Opinion in Genetics & Development. Elsevier. https://doi.org/10.1016/j.gde.2017.03.010
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| PubMed | Europe PMC
2017 | Published | Journal Article | IST-REx-ID: 1163
Wysokiński, M., & Kaczmarczyk, J. (2017). Unconventional superconductivity in generalized Hubbard model role of electron–hole symmetry breaking terms. Journal of Physics: Condensed Matter. IOP Publishing. https://doi.org/10.1088/1361-648X/aa532f
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2017 | Published | Journal Article | IST-REx-ID: 1007 |
Lang, M., & Sontag, E. (2017). Zeros of nonlinear systems with input invariances. Automatica. International Federation of Automatic Control. https://doi.org/10.1016/j.automatica.2017.03.030
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2017 | Published | Conference Paper | IST-REx-ID: 6517 |
Fulek, R. (2017). Embedding graphs into embedded graphs (Vol. 92). Presented at the ISAAC: International Symposium on Algorithms and Computation, Phuket, Thailand: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPICS.ISAAC.2017.34
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2017 | Published | Journal Article | IST-REx-ID: 730
Savin, C., & Tkačik, G. (2017). Maximum entropy models as a tool for building precise neural controls. Current Opinion in Neurobiology. Elsevier. https://doi.org/10.1016/j.conb.2017.08.001
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2017 | Published | Conference Paper | IST-REx-ID: 683 |
Lubiw, A., Masárová, Z., & Wagner, U. (2017). A proof of the orbit conjecture for flipping edge labelled triangulations (Vol. 77). Presented at the SoCG: Symposium on Computational Geometry, Brisbane, Australia: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.SoCG.2017.49
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2017 | Published | Conference Paper | IST-REx-ID: 911 |
Royer, A., Kolesnikov, A., & Lampert, C. (2017). Probabilistic image colorization (p. 85.1-85.12). Presented at the BMVC: British Machine Vision Conference, London, United Kingdom: BMVA Press. https://doi.org/10.5244/c.31.85
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| arXiv
2017 | Published | Conference Paper | IST-REx-ID: 1000 |
Kolesnikov, A., & Lampert, C. (2017). PixelCNN models with auxiliary variables for natural image modeling. In 34th International Conference on Machine Learning (Vol. 70, pp. 1905–1914). Sydney, Australia: JMLR.
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| arXiv
2017 | Published | Conference Paper | IST-REx-ID: 1108 |
Zimin, A., & Lampert, C. (2017). Learning theory for conditional risk minimization (Vol. 54, pp. 213–222). Presented at the AISTATS: Artificial Intelligence and Statistics, Fort Lauderdale, FL, United States: ML Research Press.
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2017 | Published | Conference Paper | IST-REx-ID: 6841 |
Martius, G. S., & Lampert, C. (2017). Extrapolation and learning equations. In 5th International Conference on Learning Representations, ICLR 2017 - Workshop Track Proceedings. Toulon, France: International Conference on Learning Representations.
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| arXiv
2017 | Published | Journal Article | IST-REx-ID: 1199 |
Barton, N. H. (2017). How does epistasis influence the response to selection? Heredity. Nature Publishing Group. https://doi.org/10.1038/hdy.2016.109
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