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238 Publications
2021 | Journal Article | IST-REx-ID: 9558 |
G. Yalniz, B. Hof, and N. B. Budanur, “Coarse graining the state space of a turbulent flow using periodic orbits,” Physical Review Letters, vol. 126, no. 24. American Physical Society, 2021.
[Preprint]
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| arXiv
2021 | Journal Article | IST-REx-ID: 9818 |
G. Sperl, R. Narain, and C. Wojtan, “Mechanics-aware deformation of yarn pattern geometry,” ACM Transactions on Graphics, vol. 40, no. 4. Association for Computing Machinery, 2021.
[Published Version]
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2021 | Scientific Software | IST-REx-ID: 9327 |
G. Sperl, R. Narain, and C. Wojtan, “Mechanics-Aware Deformation of Yarn Pattern Geometry (Additional Animation/Model Data).” IST Austria, 2021.
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2021 | Journal Article | IST-REx-ID: 9891 |
A. B. Lauritsen, “Floating Wigner crystal and periodic jellium configurations,” Journal of Mathematical Physics, vol. 62, no. 8. AIP Publishing, 2021.
[Published Version]
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| arXiv
2021 | Journal Article | IST-REx-ID: 9903 |
V. Karle, M. Serbyn, and A. Michailidis, “Area-law entangled eigenstates from nullspaces of local Hamiltonians,” Physical Review Letters, vol. 127, no. 6. American Physical Society, 2021.
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| arXiv
2021 | Conference Paper | IST-REx-ID: 10666 |
M. Lechner, R. Hasani, R. Grosu, D. Rus, and T. A. Henzinger, “Adversarial training is not ready for robot learning,” in 2021 IEEE International Conference on Robotics and Automation, Xi’an, China, 2021, pp. 4140–4147.
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| arXiv
2021 | Journal Article | IST-REx-ID: 9121 |
A. B. Lauritsen, “The BCS energy gap at low density,” Letters in Mathematical Physics, vol. 111. Springer Nature, 2021.
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2021 | Thesis | IST-REx-ID: 9056 |
G. F. Osang, “Multi-cover persistence and Delaunay mosaics,” Institute of Science and Technology Austria, Klosterneuburg, 2021.
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2021 | Thesis | IST-REx-ID: 9022 |
G. Cipolloni, “Fluctuations in the spectrum of random matrices,” Institute of Science and Technology Austria, 2021.
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2021 | Conference Paper | IST-REx-ID: 9416 |
M. Phuong and C. Lampert, “The inductive bias of ReLU networks on orthogonally separable data,” in 9th International Conference on Learning Representations, Virtual, 2021.
[Published Version]
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