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40 Publications

2019 | Conference Paper | IST-REx-ID: 6642   OA
M. Dostalík, V. Průša, and T. Skrivan, “On diffusive variants of some classical viscoelastic rate-type models,” in AIP Conference Proceedings, Zlin, Czech Republic, 2019, vol. 2107, p. 020002.
View | DOI | Download (ext.) | arXiv
 
2019 | Journal Article | IST-REx-ID: 7002
I. Kondapaneni, P. Vevoda, P. Grittmann, T. Skrivan, P. Slusallek, and J. Křivánek, “Optimal multiple importance sampling,” ACM Transactions on Graphics, vol. 38, no. 4, p. 37, 2019.
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2019 | Journal Article | IST-REx-ID: 6442   OA
C. Schreck, C. Hafner, and C. J. Wojtan, “Fundamental solutions for water wave animation,” ACM Transactions on Graphics, vol. 38, no. 4, p. 130, 2019.
View | Files available | DOI
 
2018 | Journal Article | IST-REx-ID: 134   OA
S. Jeschke, T. Skrivan, M. Mueller Fischer, N. Chentanez, M. Macklin, and C. J. Wojtan, “Water surface wavelets,” ACM Transactions on Graphics, vol. 37, no. 4, p. 94, 2018.
View | Files available | DOI
 
2018 | Journal Article | IST-REx-ID: 135
T. Sato, C. J. Wojtan, N. Thuerey, T. Igarashi, and R. Ando, “Extended narrow band FLIP for liquid simulations,” Computer Graphics Forum, vol. 37, no. 2, pp. 169–177, 2018.
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2018 | Journal Article | IST-REx-ID: 5681
I. Hikaru, C. J. Wojtan, N. Thuerey, T. Igarashi, and R. Ando, “Simulating Liquids on Dynamically Warping Grids,” IEEE Transactions on Visualization and Computer Graphics, p. 1.
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2017 | Journal Article | IST-REx-ID: 670
C. Schreck, D. Rohmer, and S. Hahmann, “Interactive paper tearing,” Computer Graphics Forum, vol. 36, no. 2, pp. 95–106, 2017.
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2017 | Thesis | IST-REx-ID: 839   OA
D. Hahn, Brittle fracture simulation with boundary elements for computer graphics. IST Austria, 2017.
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2017 | Research Data | IST-REx-ID: 5568
D. Hahn, Source codes: Brittle fracture simulation with boundary elements for computer graphics. IST Austria, 2017.
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2017 | Conference Paper | IST-REx-ID: 998   OA
S. A. Rebuffi, A. Kolesnikov, G. Sperl, and C. Lampert, “iCaRL: Incremental classifier and representation learning,” presented at the CVPR: Computer Vision and Pattern Recognition, Honolulu, HA, United States, 2017, vol. 2017, pp. 5533–5542.
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