Gusak, Julia

9 publications

ICML 2025 HiRemate: Hierarchical Approach for Efficient Re-Materialization of Neural Networks Julia Gusak, Xunyi Zhao, Théotime Le Hellard, Zhe Li, Lionel Eyraud-Dubois, Olivier Beaumont

JAIR 2024 Quantization Aware Factorization for Deep Neural Network Compression Daria Cherniuk, Stanislav Abukhovich, Anh Huy Phan, Ivan V. Oseledets, Andrzej Cichocki, Julia Gusak

ICML 2023 Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction Georgii Sergeevich Novikov, Daniel Bershatsky, Julia Gusak, Alex Shonenkov, Denis Valerievich Dimitrov, Ivan Oseledets

ICML 2023 Rockmate: An Efficient, Fast, Automatic and Generic Tool for Re-Materialization in PyTorch Xunyi Zhao, Théotime Le Hellard, Lionel Eyraud-Dubois, Julia Gusak, Olivier Beaumont

IJCAI 2022 Survey on Efficient Training of Large Neural Networks Julia Gusak, Daria Cherniuk, Alena Shilova, Alexandr Katrutsa, Daniel Bershatsky, Xunyi Zhao, Lionel Eyraud-Dubois, Oleh Shliazhko, Denis Dimitrov, Ivan V. Oseledets, Olivier Beaumont

NeurIPS 2020 Interpolation Technique to Speed up Gradients Propagation in Neural ODEs Talgat Daulbaev, Alexandr Katrutsa, Larisa Markeeva, Julia Gusak, Andrzej Cichocki, Ivan Oseledets

ECCV 2020 Stable Low-Rank Tensor Decomposition for Compression of Convolutional Neural Network Anh-Huy Phan, Konstantin Sobolev, Konstantin Sozykin, Dmitry Ermilov, Julia Gusak, Petr Tichavský, Valeriy Glukhov, Ivan Oseledets, Andrzej Cichocki

ICLRW 2020 Towards Understanding Normalization in Neural ODEs Julia Gusak, Larisa Markeeva, Talgat Daulbaev, Alexander Katrutsa, Andrzej Cichocki, Ivan Oseledets

ICCVW 2019 Automated Multi-Stage Compression of Neural Networks Julia Gusak, Maksym Kholyavchenko, Evgeny Ponomarev, Larisa Markeeva, Philip Blagoveschensky, Andrzej Cichocki, Ivan V. Oseledets