Zobrazeno 1 - 10
of 25 204
pro vyhledávání: '"A Gorbunov"'
Controlling the spectral norm of the Jacobian matrix, which is related to the convolution operation, has been shown to improve generalization, training stability and robustness in CNNs. Existing methods for computing the norm either tend to overestim
Externí odkaz:
http://arxiv.org/abs/2409.11859
Autor:
Gorbunov, Dmitry, Kriukova, Ekaterina
We study the production of hypothetical vector particles, dark photons $\gamma^\prime$, with masses in the the range 0.4--1.8 GeV via inelastic proton bremsstrahlung. We further develop the approach of Refs. [1-3], where for the first time we conside
Externí odkaz:
http://arxiv.org/abs/2409.11386
Autor:
Gorbunov, Dmitry, Kriukova, Ekaterina
We study the production of vector portal mediators, dark photons, with masses in the range 0.4--1.8\,GeV in proton-proton collisions via the process of inelastic proton bremsstrahlung. In contrast to previous studies, we take into account the contrib
Externí odkaz:
http://arxiv.org/abs/2409.11089
In this paper we present new constraints on velocity-independent cross section of keV-scale mass annihilating Dark Matter particles obtained with SRG/ART-XC after 4 full-sky surveys. These constraints are derived from observations of the Milky Way Ha
Externí odkaz:
http://arxiv.org/abs/2407.18371
Publikováno v:
JCAP09(2024)047
Employing the publicly available CosmoLattice code, we conduct numerical simulations of a domain wall network and the resulting gravitational waves (GWs) in a radiation-dominated Universe in the $Z_2$-symmetric scalar field model. In particular, the
Externí odkaz:
http://arxiv.org/abs/2406.17053
Autor:
Moskvoretskii, Viktor, Tupitsa, Nazarii, Biemann, Chris, Horváth, Samuel, Gorbunov, Eduard, Nikishina, Irina
We present a new approach based on the Personalized Federated Learning algorithm MeritFed that can be applied to Natural Language Tasks with heterogeneous data. We evaluate it on the Low-Resource Machine Translation task, using the dataset from the L
Externí odkaz:
http://arxiv.org/abs/2406.12564
Autor:
Gorbunov, Mikhail, Yudin, Nikolay, Soboleva, Vera, Alanov, Aibek, Naumov, Alexey, Rakhuba, Maxim
The increasing size of neural networks has led to a growing demand for methods of efficient fine-tuning. Recently, an orthogonal fine-tuning paradigm was introduced that uses orthogonal matrices for adapting the weights of a pretrained model. In this
Externí odkaz:
http://arxiv.org/abs/2406.10019
Autor:
Zainutdinov, D. I., Borodin, V. A., Gorbunov, S. A., Medvedev, N., Rymzhanov, R. A., Sorokin, M. V., Voronkov, R. A., Volkov, A. E.
At ambient conditions, SiC is known to be resistant to irradiation with swift heavy ions (SHI) decelerating in the electronic stopping regime. However, there is no experimental data on the SiC irradiation at elevated temperatures. To investigate this
Externí odkaz:
http://arxiv.org/abs/2406.07963
Autor:
Chezhegov, Savelii, Klyukin, Yaroslav, Semenov, Andrei, Beznosikov, Aleksandr, Gasnikov, Alexander, Horváth, Samuel, Takáč, Martin, Gorbunov, Eduard
Methods with adaptive stepsizes, such as AdaGrad and Adam, are essential for training modern Deep Learning models, especially Large Language Models. Typically, the noise in the stochastic gradients is heavy-tailed for the later ones. Gradient clippin
Externí odkaz:
http://arxiv.org/abs/2406.04443
Using tremendous photon statistics gained with the stray light aperture of the NuSTAR telescope over 11 years of operation, we set strong limits on the emission of close to monochromatic photons from the radiative decays of putative dark matter steri
Externí odkaz:
http://arxiv.org/abs/2405.17861