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Julia Gusak
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2020 – today
- 2024
- [j3]Daria Cherniuk, Stanislav Abukhovich, Anh Huy Phan, Ivan V. Oseledets, Andrzej Cichocki, Julia Gusak:
Quantization Aware Factorization for Deep Neural Network Compression. J. Artif. Intell. Res. 81: 973-988 (2024) - 2023
- [c7]Georgii Sergeevich Novikov, Daniel Bershatsky, Julia Gusak, Alex Shonenkov, Denis Valerievich Dimitrov, Ivan V. Oseledets:
Few-bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction. ICML 2023: 26363-26381 - [c6]Xunyi Zhao, Théotime Le Hellard, Lionel Eyraud-Dubois, Julia Gusak, Olivier Beaumont:
Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorch. ICML 2023: 42018-42045 - [c5]Viktoria Chekalina, Georgiy Novikov, Julia Gusak, Alexander Panchenko, Ivan V. Oseledets:
Efficient GPT Model Pre-training using Tensor Train Matrix Representation. PACLIC 2023: 600-608 - [i13]Viktoria Chekalina, Georgii S. Novikov, Julia Gusak, Ivan V. Oseledets, Alexander Panchenko:
Efficient GPT Model Pre-training using Tensor Train Matrix Representation. CoRR abs/2306.02697 (2023) - [i12]Xunyi Zhao, Théotime Le Hellard, Lionel Eyraud, Julia Gusak, Olivier Beaumont:
Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorch. CoRR abs/2307.01236 (2023) - [i11]Daria Cherniuk, Stanislav Abukhovich, Anh Huy Phan, Ivan V. Oseledets, Andrzej Cichocki, Julia Gusak:
Quantization Aware Factorization for Deep Neural Network Compression. CoRR abs/2308.04595 (2023) - 2022
- [c4]Julia Gusak, Daria Cherniuk, Alena Shilova, Alexandr Katrutsa, Daniel Bershatsky, Xunyi Zhao, Lionel Eyraud-Dubois, Oleh Shliazhko, Denis Dimitrov, Ivan V. Oseledets, Olivier Beaumont:
Survey on Efficient Training of Large Neural Networks. IJCAI 2022: 5494-5501 - [i10]Daniel Bershatsky, Aleksandr Mikhalev, Alexandr Katrutsa, Julia Gusak, Daniil Merkulov, Ivan V. Oseledets:
Memory-Efficient Backpropagation through Large Linear Layers. CoRR abs/2201.13195 (2022) - [i9]Georgii S. Novikov, Daniel Bershatsky, Julia Gusak, Alex Shonenkov, Denis Dimitrov, Ivan V. Oseledets:
Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction. CoRR abs/2202.00441 (2022) - [i8]Julia Gusak, Daria Cherniuk, Alena Shilova, Alexandr Katrutsa, Daniel Bershatsky, Xunyi Zhao, Lionel Eyraud-Dubois, Oleg Shlyazhko, Denis Dimitrov, Ivan V. Oseledets, Olivier Beaumont:
Survey on Large Scale Neural Network Training. CoRR abs/2202.10435 (2022) - 2021
- [i7]Julia Gusak, Alexandr Katrutsa, Talgat Daulbaev, Andrzej Cichocki, Ivan V. Oseledets:
Meta-Solver for Neural Ordinary Differential Equations. CoRR abs/2103.08561 (2021) - 2020
- [j2]Chunfeng Cui
, Kaiqi Zhang, Talgat Daulbaev, Julia Gusak, Ivan V. Oseledets, Zheng Zhang:
Active Subspace of Neural Networks: Structural Analysis and Universal Attacks. SIAM J. Math. Data Sci. 2(4): 1096-1122 (2020) - [c3]Anh Huy Phan
, Konstantin Sobolev, Konstantin Sozykin, Dmitry Ermilov, Julia Gusak, Petr Tichavský, Valeriy Glukhov, Ivan V. Oseledets, Andrzej Cichocki:
Stable Low-Rank Tensor Decomposition for Compression of Convolutional Neural Network. ECCV (29) 2020: 522-539 - [c2]Talgat Daulbaev, Alexandr Katrutsa, Larisa Markeeva, Julia Gusak, Andrzej Cichocki, Ivan V. Oseledets:
Interpolation Technique to Speed Up Gradients Propagation in Neural ODEs. NeurIPS 2020 - [i6]Talgat Daulbaev, Alexandr Katrutsa, Larisa Markeeva, Julia Gusak, Andrzej Cichocki, Ivan V. Oseledets:
Interpolated Adjoint Method for Neural ODEs. CoRR abs/2003.05271 (2020) - [i5]Julia Gusak, Larisa Markeeva, Talgat Daulbaev, Alexandr Katrutsa, Andrzej Cichocki, Ivan V. Oseledets:
Towards Understanding Normalization in Neural ODEs. CoRR abs/2004.09222 (2020) - [i4]Anh Huy Phan, Konstantin Sobolev, Konstantin Sozykin, Dmitry Ermilov, Julia Gusak, Petr Tichavský, Valeriy Glukhov, Ivan V. Oseledets, Andrzej Cichocki:
Stable Low-rank Tensor Decomposition for Compression of Convolutional Neural Network. CoRR abs/2008.05441 (2020)
2010 – 2019
- 2019
- [c1]Julia Gusak, Maksym Kholyavchenko
, Evgeny Ponomarev
, Larisa Markeeva, Philip Blagoveschensky, Andrzej Cichocki, Ivan V. Oseledets:
Automated Multi-Stage Compression of Neural Networks. ICCV Workshops 2019: 2501-2508 - [i3]Julia Gusak, Maksym Kholyavchenko
, Evgeny Ponomarev, Larisa Markeeva, Ivan V. Oseledets, Andrzej Cichocki:
One time is not enough: iterative tensor decomposition for neural network compression. CoRR abs/1903.09973 (2019) - [i2]Talgat Daulbaev, Julia Gusak, Evgeny Ponomarev, Andrzej Cichocki, Ivan V. Oseledets:
Reduced-Order Modeling of Deep Neural Networks. CoRR abs/1910.06995 (2019) - [i1]Chunfeng Cui, Kaiqi Zhang, Talgat Daulbaev, Julia Gusak, Ivan V. Oseledets, Zheng Zhang:
Active Subspace of Neural Networks: Structural Analysis and Universal Attacks. CoRR abs/1910.13025 (2019) - 2016
- [j1]Ekaterina Bulinskaya, Julia Gusak:
Optimal Control and Sensitivity Analysis for Two Risk Models. Commun. Stat. Simul. Comput. 45(5): 1451-1466 (2016)
Coauthor Index

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