3 Publications

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[3]
2024 | Published | Conference Paper | IST-REx-ID: 18975 | OA
I.-V. Modoranu, A. Kalinov, E. Kurtic, E. Frantar, and D.-A. Alistarh, “Error feedback can accurately compress preconditioners,” in 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 35910–35933.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[2]
2024 | Published | Journal Article | IST-REx-ID: 17219 | OA
P. Synak, A. Kalinov, I.-M. Strugaru, A. Etemadi, H. Yang, and C. Wojtan, “Multi-material mesh-based surface tracking with implicit topology changes,” ACM Transactions on Graphics, vol. 43, no. 4. Association for Computing Machinery, 2024.
[Published Version] View | Files available | DOI
 
[1]
2022 | Published | Journal Article | IST-REx-ID: 11556 | OA
A. Kalinov, A. I. Osinskiy, S. A. Matveev, W. Otieno, and N. V. Brilliantov, “Direct simulation Monte Carlo for new regimes in aggregation-fragmentation kinetics,” Journal of Computational Physics, vol. 467. Elsevier, 2022.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

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3 Publications

Mark all

[3]
2024 | Published | Conference Paper | IST-REx-ID: 18975 | OA
I.-V. Modoranu, A. Kalinov, E. Kurtic, E. Frantar, and D.-A. Alistarh, “Error feedback can accurately compress preconditioners,” in 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 35910–35933.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[2]
2024 | Published | Journal Article | IST-REx-ID: 17219 | OA
P. Synak, A. Kalinov, I.-M. Strugaru, A. Etemadi, H. Yang, and C. Wojtan, “Multi-material mesh-based surface tracking with implicit topology changes,” ACM Transactions on Graphics, vol. 43, no. 4. Association for Computing Machinery, 2024.
[Published Version] View | Files available | DOI
 
[1]
2022 | Published | Journal Article | IST-REx-ID: 11556 | OA
A. Kalinov, A. I. Osinskiy, S. A. Matveev, W. Otieno, and N. V. Brilliantov, “Direct simulation Monte Carlo for new regimes in aggregation-fragmentation kinetics,” Journal of Computational Physics, vol. 467. Elsevier, 2022.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

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