Zobrazeno 1 - 10
of 563
pro vyhledávání: '"Smirnov Oleg"'
Autor:
Perkins, Simon J., Kenyon, Jonathan S., Andati, Lexy A. L., Bester, Hertzog L., Smirnov, Oleg M., Hugo, Benjamin V.
New radio interferometers such as MeerKAT, SKA, ngVLA, and DSA-2000 drive advancements in software for two key reasons. First, handling the vast data from these instruments requires subdivision and multi-node processing. Second, their improved sensit
Externí odkaz:
http://arxiv.org/abs/2412.12052
Autor:
Smirnov, Oleg M., Makhathini, Sphesihle, Kenyon, Jonathan S., Bester, Hertzog L., Perkins, Simon J., Ramaila, Athanaseus J. T., Hugo, Benjamin V.
Stimela2 is a new-generation framework for developing data reduction workflows. It is designed for radio astronomy data but can be adapted for other data processing applications. Stimela2 aims at the middle ground between ease of development, human r
Externí odkaz:
http://arxiv.org/abs/2412.10080
Autor:
Kenyon, Jonathan S., Perkins, Simon J., Bester, Hertzog L., Smirnov, Oleg M., Russeeawon, Cyndie, Hugo, Benjamin V.
Calibration of radio interferometer data ought to be a solved problem; it has been an integral part of data reduction for some time. However, as larger, more sensitive radio interferometers are conceived and built, the calibration problem grows in bo
Externí odkaz:
http://arxiv.org/abs/2412.10072
Autor:
Bester, Hertzog L., Kenyon, Jonathan S., Repetti, Audrey, Perkins, Simon J., Smirnov, Oleg M., Blecher, Tariq, Mhiri, Yassine, Roth, Jakob, Heywood, Ian, Wiaux, Yves, Hugo, Benjamin V.
The popularity of the CLEAN algorithm in radio interferometric imaging stems from its maturity, speed, and robustness. While many alternatives have been proposed in the literature, none have achieved mainstream adoption by astronomers working with da
Externí odkaz:
http://arxiv.org/abs/2412.10073
Autor:
Ennadir, Sofiane, Gandler, Gabriela Zarzar, Cornell, Filip, Cao, Lele, Smirnov, Oleg, Wang, Tianze, Zólyomi, Levente, Brinne, Björn, Asadi, Sahar
Graphs are ubiquitous in real-world applications, ranging from social networks to biological systems, and have inspired the development of Graph Neural Networks (GNNs) for learning expressive representations. While most research has centered on stati
Externí odkaz:
http://arxiv.org/abs/2412.03783
Autor:
Wang, Tianze, Honari-Jahromi, Maryam, Katsarou, Styliani, Mikheeva, Olga, Panagiotakopoulos, Theodoros, Smirnov, Oleg, Cao, Lele, Asadi, Sahar
This pilot study explores the application of language models (LMs) to model game event sequences, treating them as a customized natural language. We investigate a popular mobile game, transforming raw event data into textual sequences and pretraining
Externí odkaz:
http://arxiv.org/abs/2410.18605
CIZA J2242.8+5301, or the Sausage cluster, is well studied over a range of frequencies. Since its first discovery, a lot of interesting features and unique characteristics have been uncovered. In this work, we report some more new morphological featu
Externí odkaz:
http://arxiv.org/abs/2409.07504
Autor:
Roth, Jakob, Frank, Philipp, Bester, Hertzog L., Smirnov, Oleg M., Westermann, Rüdiger, Enßlin, Torsten A.
Publikováno v:
A&A 690, A387 (2024)
Context: Interferometric imaging is algorithmically and computationally challenging as there is no unique inversion from the measurement data back to the sky maps, and the datasets can be very large. Many imaging methods already exist, but most of th
Externí odkaz:
http://arxiv.org/abs/2406.09144
Autor:
Smirnov, Oleg, Polisi, Labinot
In this paper, we introduce the Behavior Structformer, a method for modeling user behavior using structured tokenization within a Transformer-based architecture. By converting tracking events into dense tokens, this approach enhances model training e
Externí odkaz:
http://arxiv.org/abs/2406.05274
Autor:
Titov, Sergey, Evtikhiev, Mikhail, Shapkin, Anton, Smirnov, Oleg, Boytsov, Sergei, Karaeva, Dariia, Sheptyakov, Maksim, Arkhipov, Mikhail, Bryksin, Timofey, Bogomolov, Egor
In this technical report, we present three novel datasets of Kotlin code: KStack, KStack-clean, and KExercises. We also describe the results of fine-tuning CodeLlama and DeepSeek models on this data. Additionally, we present a version of the HumanEva
Externí odkaz:
http://arxiv.org/abs/2405.19250