Follow
Ekaterina Lobacheva
Ekaterina Lobacheva
HSE University / bayesgroup.ru
Verified email at hse.ru - Homepage
Title
Cited by
Cited by
Year
On power laws in deep ensembles
E Lobacheva, N Chirkova, M Kodryan, DP Vetrov
Advances in Neural Information Processing Systems 33, 2375-2385, 2020
442020
On the periodic behavior of neural network training with batch normalization and weight decay
E Lobacheva, M Kodryan, N Chirkova, A Malinin, DP Vetrov
Advances in Neural Information Processing Systems 34, 21545-21556, 2021
222021
Bayesian sparsification of recurrent neural networks
E Lobacheva, N Chirkova, D Vetrov
arXiv preprint arXiv:1708.00077, 2017
192017
Bayesian compression for natural language processing
N Chirkova, E Lobacheva, D Vetrov
arXiv preprint arXiv:1810.10927, 2018
162018
Automated real-time classification of functional states based on physiological parameters
EM Lobacheva, YN Galatenko, RF Gabidullina, VV Galatenko, ED Livshitz, ...
Procedia-Social and Behavioral Sciences 86, 373-378, 2013
112013
Semantic embeddings for program behavior patterns
A Chistyakov, E Lobacheva, A Kuznetsov, A Romanenko
arXiv preprint arXiv:1804.03635, 2018
92018
Training scale-invariant neural networks on the sphere can happen in three regimes
M Kodryan, E Lobacheva, M Nakhodnov, DP Vetrov
Advances in Neural Information Processing Systems 35, 14058-14070, 2022
82022
Deep ensembles on a fixed memory budget: One wide network or several thinner ones?
N Chirkova, E Lobacheva, D Vetrov
arXiv preprint arXiv:2005.07292, 2020
82020
Structured sparsification of gated recurrent neural networks
E Lobacheva, N Chirkova, A Markovich, D Vetrov
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4989-4996, 2020
82020
automated real-time classification of functional states: significance of individual tuning stage
MG Ya, E Podol’Skii Vladimir
Psychology in Russia: State of the art 6 (3), 41-48, 2013
82013
Joint optimization of segmentation and color clustering
E Lobacheva, O Veksler, Y Boykov
Proceedings of the IEEE International Conference on Computer Vision, 1626-1634, 2015
72015
Bayesian sparsification of gated recurrent neural networks
E Lobacheva, N Chirkova, D Vetrov
arXiv preprint arXiv:1812.05692, 2018
42018
Deep part-based generative shape model with latent variables
A Kirillov, M Gavrikov, E Lobacheva, A Osokin, D Vetrov
27th British Machine Vision Conference (BMVC 2016), 2016
32016
Monotonic models for real-time dynamic malware detection
A Chistyakov, E Lobacheva, A Shevelev, A Romanenko
arXiv preprint arXiv:1804.03643, 2018
22018
Loss function dynamics and landscape for deep neural networks trained with quadratic loss
MS Nakhodnov, MS Kodryan, EM Lobacheva, DS Vetrov
Doklady Mathematics 106 (Suppl 1), S43-S62, 2022
12022
On the memorization properties of contrastive learning
I Sadrtdinov, N Chirkova, E Lobacheva
arXiv preprint arXiv:2107.10143, 2021
12021
Adaptive prediction time for sequence classification
M Ryabinin, E Lobacheva
12018
To Stay or Not to Stay in the Pre-train Basin: Insights on Ensembling in Transfer Learning
I Sadrtdinov, D Pozdeev, DP Vetrov, E Lobacheva
Advances in Neural Information Processing Systems 36, 2024
2024
Large Learning Rates Improve Generalization: But How Large Are We Talking About?
E Lobacheva, E Pockonechnyy, M Kodryan, D Vetrov
arXiv preprint arXiv:2311.11303, 2023
2023
Electronic apparatus for compressing recurrent neural network and method thereof
EM Lobacheva, NA Chirkova, DP Vetrov
US Patent 11,568,237, 2023
2023
The system can't perform the operation now. Try again later.
Articles 1–20