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4950 Publications


2021 | Thesis | IST-REx-ID: 10007 | OA
Hensel, S. (2021). Curvature driven interface evolution: Uniqueness properties of weak solution concepts. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10007
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2021 | Journal Article | IST-REx-ID: 10191 | OA
Bui, T. L., Chatterjee, K., Gautam, T., Pavlogiannis, A., & Toman, V. (2021). The reads-from equivalence for the TSO and PSO memory models. Proceedings of the ACM on Programming Languages. Association for Computing Machinery. https://doi.org/10.1145/3485541
[Published Version] View | Files available | DOI | arXiv
 

2021 | Preprint | IST-REx-ID: 10013 | OA
Hensel, S., & Laux, T. (n.d.). Weak-strong uniqueness for the mean curvature flow of double bubbles. arXiv. https://doi.org/10.48550/arXiv.2108.01733
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2021 | Journal Article | IST-REx-ID: 9928 | OA
Peruzzo, M., Hassani, F., Szep, G., Trioni, A., Redchenko, E., Zemlicka, M., & Fink, J. M. (2021). Geometric superinductance qubits: Controlling phase delocalization across a single Josephson junction. PRX Quantum. American Physical Society. https://doi.org/10.1103/PRXQuantum.2.040341
[Published Version] View | Files available | DOI | WoS | arXiv
 

2021 | Thesis | IST-REx-ID: 10030 | OA
Portinale, L. (2021). Discrete-to-continuum limits of transport problems and gradient flows in the space of measures. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10030
[Published Version] View | Files available | DOI
 

2021 | Thesis | IST-REx-ID: 9920 | OA
Peruzzo, M. (2021). Geometric superinductors and their applications in circuit quantum electrodynamics. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:9920
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2021 | Conference Paper | IST-REx-ID: 10432 | OA
Nadiradze, G., Markov, I., Chatterjee, B., Kungurtsev, V., & Alistarh, D.-A. (2021). Elastic consistency: A practical consistency model for distributed stochastic gradient descent. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, pp. 9037–9045). Virtual.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

2021 | Conference Paper | IST-REx-ID: 10041 | OA
Kamath Hosdurg, C., Klein, K., Pietrzak, K. Z., & Wichs, D. (2021). Limits on the Adaptive Security of Yao’s Garbling. In 41st Annual International Cryptology Conference, Part II (Vol. 12826, pp. 486–515). Cham: Springer Nature. https://doi.org/10.1007/978-3-030-84245-1_17
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2021 | Conference Paper | IST-REx-ID: 10049 | OA
Klein, K., Pascual Perez, G., Walter, M., Kamath Hosdurg, C., Capretto, M., Cueto Noval, M., … Pietrzak, K. Z. (2021). Keep the dirt: tainted TreeKEM, adaptively and actively secure continuous group key agreement. In 2021 IEEE Symposium on Security and Privacy (pp. 268–284). San Francisco, CA, United States: IEEE. https://doi.org/10.1109/sp40001.2021.00035
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2021 | Conference Paper | IST-REx-ID: 10044 | OA
Kamath Hosdurg, C., Klein, K., & Pietrzak, K. Z. (2021). On treewidth, separators and Yao’s garbling. In 19th Theory of Cryptography Conference 2021. Raleigh, NC, United States: International Association for Cryptologic Research.
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2021 | Thesis | IST-REx-ID: 10422 | OA
Piankov, A. (2021). Towards designer materials using customizable particle shape. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10422
[Published Version] View | Files available | DOI
 

2021 | Preprint | IST-REx-ID: 10803 | OA
Konstantinov, N. H., & Lampert, C. (n.d.). Fairness through regularization for learning to rank. arXiv. https://doi.org/10.48550/arXiv.2102.05996
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2021 | Preprint | IST-REx-ID: 10762 | OA
Rzadkowski, W., Lemeshko, M., & Mentink, J. H. (n.d.). Artificial neural network states for non-additive systems. arXiv. https://doi.org/10.48550/arXiv.2105.15193
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2021 | Thesis | IST-REx-ID: 9418 | OA
Phuong, M. (2021). Underspecification in deep learning. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:9418
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2021 | Preprint | IST-REx-ID: 14278 | OA
Koval, I. (n.d.). Local strong Birkhoff conjecture and local spectral rigidity of almost every ellipse. arXiv. https://doi.org/10.48550/ARXIV.2111.12171
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2021 | Thesis | IST-REx-ID: 10199 | OA
Toman, V. (2021). Improved verification techniques for concurrent systems. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:10199
[Published Version] View | Files available | DOI
 

2021 | Journal Article | IST-REx-ID: 8429 | OA
Patxot, M., Trejo Banos, D., Kousathanas, A., Orliac, E. J., Ojavee, S. E., Moser, G., … Robinson, M. R. (2021). Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-021-27258-9
[Published Version] View | Files available | DOI | WoS
 

2021 | Conference Paper | IST-REx-ID: 10854 | OA
Foerster, K.-T., Korhonen, J., Paz, A., Rybicki, J., & Schmid, S. (2021). Input-dynamic distributed algorithms for communication networks. In Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems (pp. 71–72). Virtual, Online: Association for Computing Machinery. https://doi.org/10.1145/3410220.3453923
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2021 | Journal Article | IST-REx-ID: 10855 | OA
Foerster, K.-T., Korhonen, J., Paz, A., Rybicki, J., & Schmid, S. (2021). Input-dynamic distributed algorithms for communication networks. Proceedings of the ACM on Measurement and Analysis of Computing Systems. Association for Computing Machinery. https://doi.org/10.1145/3447384
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2021 | Journal Article | IST-REx-ID: 9293 | OA
Chatterjee, K., Dvořák, W., Henzinger, M. H., & Svozil, A. (2021). Algorithms and conditional lower bounds for planning problems. Artificial Intelligence. Elsevier. https://doi.org/10.1016/j.artint.2021.103499
[Preprint] View | Files available | DOI | Download Preprint (ext.) | WoS | arXiv
 

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