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pro vyhledávání: '"Endo BY"'
Recent works on accelerating Vision-Language Models show that strong performance can be maintained across a variety of vision-language tasks despite highly compressing visual information. In this work, we examine the popular acceleration approach of
Externí odkaz:
http://arxiv.org/abs/2412.13180
Autor:
Anai, Keitaro, Suzuki, Yasunari, Tokunaga, Yuuki, Matsuzaki, Yuichiro, Takeda, Shuntaro, Endo, Suguru
Continuous-variable (CV) quantum computing is a promising candidate for quantum computation because it can, even with one mode, utilize infinite-dimensional Hilbert spaces and can efficiently handle continuous values. Although photonic platforms have
Externí odkaz:
http://arxiv.org/abs/2411.19505
Autor:
Kasahara, Yuichiro, Akinari, Kota, Kouno, Tomoya, Sano, Noriko, Abe, Taro, Yamauchi, Genki, Endo, Daisuke, Hashimoto, Takeshi, Nagatani, Keiji, Kurazume, Ryo
In recent years, labor shortages due to the declining birthrate and aging population have become significant challenges at construction sites in developed countries, including Japan. To address these challenges, we are developing an open platform cal
Externí odkaz:
http://arxiv.org/abs/2412.00147
Autor:
Endo, Katsuhiro, Takahashi, Kazuaki Z.
From weather to neural networks, modeling is not only useful for understanding various phenomena, but also has a wide range of potential applications. Although nonlinear differential equations are extremely useful tools in modeling, their solutions a
Externí odkaz:
http://arxiv.org/abs/2411.16233
Autor:
Zhuang, Chen, Chen, Peng, Liu, Xin, Yokota, Rio, Dryden, Nikoli, Endo, Toshio, Matsuoka, Satoshi, Wahib, Mohamed
Graph Convolutional Networks (GCNs) are widely used in various domains. However, training distributed full-batch GCNs on large-scale graphs poses challenges due to inefficient memory access patterns and high communication overhead. This paper present
Externí odkaz:
http://arxiv.org/abs/2411.16025
Distributed quantum computation (DQC) is a promising approach for scalable quantum computing, where high-fidelity non-local operations among remote devices are required for universal quantum computation. These operations are typically implemented thr
Externí odkaz:
http://arxiv.org/abs/2411.10024
Autor:
Suzuki, Yudai, Aoki, Shiori, Key, Fabian, Endo, Katsuhiro, Matsuda, Yoshiki, Tanaka, Shu, Behr, Marek, Muramatsu, Mayu
Topology optimization is an essential tool in computational engineering, for example, to improve the design and efficiency of flow channels. At the same time, Ising machines, including digital or quantum annealers, have been used as efficient solvers
Externí odkaz:
http://arxiv.org/abs/2411.08405
Autor:
Takagi, Kenichiro, Moriya, Naoki, Aoki, Shiori, Endo, Katsuhiro, Muramatsu, Mayu, Fukagata, Koji
Publikováno v:
Fluid Dynamics Research (2024)
We investigate the possibility and current limitations of flow computations using quantum annealers by solving a fundamental flow problem on Ising machines. As a fundamental problem, we consider the one-dimensional advection-diffusion equation. We fo
Externí odkaz:
http://arxiv.org/abs/2411.05326
Autor:
Kaneda, Masaya, Tsuruoka, Shun, Shinya, Hikari, Fukushima, Tetsuya, Endo, Tatsuro, Tadano, Yuriko, Takeda, Takahito, Masago, Akira, Tanaka, Masaaki, Katayama-Yoshida, Hiroshi, Ohya, Shinobu
Memristors, which are characterized by their unique input-voltage-history-dependent resistance, have garnered significant attention for the exploration of next-generation in-memory computing, reconfigurable logic circuits, and neural networks. Memris
Externí odkaz:
http://arxiv.org/abs/2411.04355
Relighting of human images enables post-photography editing of lighting effects in portraits. The current mainstream approach uses neural networks to approximate lighting effects without explicitly accounting for the principle of physical shading. As
Externí odkaz:
http://arxiv.org/abs/2411.00356