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5064 Publications
2018 | Journal Article | IST-REx-ID: 458 |
A. Akopyan and A. Bobenko, “Incircular nets and confocal conics,” Transactions of the American Mathematical Society, vol. 370, no. 4. American Mathematical Society, pp. 2825–2854, 2018.
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| WoS
2018 | Conference Paper | IST-REx-ID: 5788 |
G. Avni, T. A. Henzinger, and R. Ibsen-Jensen, “Infinite-duration poorman-bidding games,” presented at the 14th International Conference on Web and Internet Economics, WINE, Oxford, UK, 2018, vol. 11316, pp. 21–36.
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| arXiv
2018 | Journal Article | IST-REx-ID: 150 |
R. Dick et al., “Inositol phosphates are assembly co-factors for HIV-1,” Nature, vol. 560, no. 7719. Nature Publishing Group, pp. 509–512, 2018.
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| PubMed | Europe PMC
2018 | Journal Article | IST-REx-ID: 303 |
N. Kalinin and M. Shkolnikov, “Introduction to tropical series and wave dynamic on them,” Discrete and Continuous Dynamical Systems- Series A, vol. 38, no. 6. AIMS, pp. 2827–2849, 2018.
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| arXiv
2018 | Conference Paper | IST-REx-ID: 14202 |
F. Locatello, G. Dresdner, R. Khanna, I. Valera, and G. Rätsch, “Boosting black box variational inference,” in Advances in Neural Information Processing Systems, Montreal, Canada, 2018, vol. 31.
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| arXiv
2018 | Conference Paper | IST-REx-ID: 14201 |
F. Locatello, R. Khanna, J. Ghosh, and G. Rätsch, “Boosting variational inference: An optimization perspective,” in Proceedings of the 21st International Conference on Artificial Intelligence and Statistics, Playa Blanca, Lanzarote, 2018, vol. 84, pp. 464–472.
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| arXiv
2018 | Conference Paper | IST-REx-ID: 14198 |
V. Fortuin, M. Hüser, F. Locatello, H. Strathmann, and G. Rätsch, “SOM-VAE: Interpretable discrete representation learning on time series,” in International Conference on Learning Representations, New Orleans, LA, United States, 2018.
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| arXiv
2018 | Conference Paper | IST-REx-ID: 14203 |
A. Yurtsever, O. Fercoq, F. Locatello, and V. Cevher, “A conditional gradient framework for composite convex minimization with applications to semidefinite programming,” in Proceedings of the 35th International Conference on Machine Learning, Stockholm, Sweden, 2018, vol. 80, pp. 5727–5736.
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| arXiv