Black-box learning of multigrid parameters A Katrutsa, T Daulbaev, I Oseledets Journal of Computational and Applied Mathematics 368, 112524, 2020 | 68* | 2020 |
Interpolation Technique to Speed Up Gradients Propagation in Neural ODEs T Daulbaev, A Katrutsa, L Markeeva, J Gusak, A Cichocki, I Oseledets Advances in Neural Information Processing Systems 33, 2020 | 41* | 2020 |
Active subspace of neural networks: Structural analysis and universal attacks C Cui, K Zhang, T Daulbaev, J Gusak, I Oseledets, Z Zhang SIAM Journal on Mathematics of Data Science 2 (4), 1096-1122, 2020 | 34 | 2020 |
Towards Understanding Normalization in Neural ODEs J Gusak, L Markeeva, T Daulbaev, A Katrutsa, A Cichocki, I Oseledets ICLR 2020 Workshop on Integration of Deep Neural Models and Differential …, 2020 | 17 | 2020 |
Reduced-order modeling of deep neural networks J Gusak, T Daulbaev, E Ponomarev, A Cichocki, I Oseledets Computational Mathematics and Mathematical Physics 61 (5), 774-785, 2021 | 10 | 2021 |
LoTR: Low Tensor Rank Weight Adaptation D Bershatsky, D Cherniuk, T Daulbaev, I Oseledets arXiv preprint arXiv:2402.01376, 2024 | 1 | 2024 |
Meta-Solver for Neural Ordinary Differential Equations J Gusak, A Katrutsa, T Daulbaev, A Cichocki, I Oseledets https://arxiv.org/abs/2103.08561, 2021 | 1 | 2021 |