Zobrazeno 1 - 10
of 60 708
pro vyhledávání: '"Nakata A"'
Autor:
Yatomi, Go, Nakata, Motoki
Convergence of a matrix decomposition technique, the multi-field singular value decomposition (MFSVD) which efficiently analyzes nonlinear correlations by simultaneously decomposing multiple fields, is investigated. Toward applications in turbulence
Externí odkaz:
http://arxiv.org/abs/2411.03739
We study unitary and state $t$-designs from a computational complexity theory perspective. First, we address the problems of computing frame potentials that characterize (approximate) $t$-designs. We provide a quantum algorithm for computing the fram
Externí odkaz:
http://arxiv.org/abs/2410.23353
Continuous normalizing flows (CNFs) can model data distributions with expressive infinite-length architectures. But this modeling involves computationally expensive process of solving an ordinary differential equation (ODE) during maximum likelihood
Externí odkaz:
http://arxiv.org/abs/2410.09246
The goal of this paper is to improve the performance of pretrained Vision Transformer (ViT) models, particularly DINOv2, in image clustering task without requiring re-training or fine-tuning. As model size increases, high-norm artifacts anomaly appea
Externí odkaz:
http://arxiv.org/abs/2410.04801
Autor:
Zhang, Yuan, Fan, Chun-Kai, Ma, Junpeng, Zheng, Wenzhao, Huang, Tao, Cheng, Kuan, Gudovskiy, Denis, Okuno, Tomoyuki, Nakata, Yohei, Keutzer, Kurt, Zhang, Shanghang
In vision-language models (VLMs), visual tokens usually consume a significant amount of computational overhead, despite their sparser information density compared to text tokens. To address this, most existing methods learn a network to prune redunda
Externí odkaz:
http://arxiv.org/abs/2410.04417
Autor:
Nakata, Atsuya, Yamanaka, Takao
Omni-directional images have been increasingly used in various applications, including virtual reality and SNS (Social Networking Services). However, their availability is comparatively limited in contrast to normal field of view (NFoV) images, since
Externí odkaz:
http://arxiv.org/abs/2409.09969
We present our system (denoted as T05) for the VoiceMOS Challenge (VMC) 2024. Our system was designed for the VMC 2024 Track 1, which focused on the accurate prediction of naturalness mean opinion score (MOS) for high-quality synthetic speech. In add
Externí odkaz:
http://arxiv.org/abs/2409.09305
Autor:
Takahashi, Ryunosuke, Guen, Yann Le, Nakata, Suguru, Igarashi, Junta, Hohlfeld, Julius, Malinowski, Grégory, Lingling, Xie, Daisuke, Kan, Shimakawa, Yuichi, Mangin, Stéphane, Wadati, Hiroki
All-optical switching (AOS) involves manipulating magnetization using only pulsed laser, presenting a promising approach for next-generation magnetic recording devices. NiCo2O4 (NCO) thin films, a rare-earth-free ferrimagnetic oxide, exhibit a high C
Externí odkaz:
http://arxiv.org/abs/2409.01615
Autor:
Ren, Pu, Nakata, Rie, Lacour, Maxime, Naiman, Ilan, Nakata, Nori, Song, Jialin, Bi, Zhengfa, Malik, Osman Asif, Morozov, Dmitriy, Azencot, Omri, Erichson, N. Benjamin, Mahoney, Michael W.
Predicting high-fidelity ground motions for future earthquakes is crucial for seismic hazard assessment and infrastructure resilience. Conventional empirical simulations suffer from sparse sensor distribution and geographically localized earthquake l
Externí odkaz:
http://arxiv.org/abs/2407.15089
In this paper, we rethink sparse lexical representations for image retrieval. By utilizing multi-modal large language models (M-LLMs) that support visual prompting, we can extract image features and convert them into textual data, enabling us to util
Externí odkaz:
http://arxiv.org/abs/2408.16296