Zobrazeno 1 - 10
of 11 763
pro vyhledávání: '"A, Jiye"'
Graph contrastive learning (GCL) has become a hot topic in the field of graph representation learning. In contrast to traditional supervised learning relying on a large number of labels, GCL exploits augmentation strategies to generate multiple views
Externí odkaz:
http://arxiv.org/abs/2412.16218
Autor:
Kim, Minkyoung, Kim, Yunha, Seo, Hyeram, Choi, Heejung, Han, Jiye, Kee, Gaeun, Ko, Soyoung, Jung, HyoJe, Kim, Byeolhee, Kim, Young-Hak, Park, Sanghyun, Jun, Tae Joon
Large language models (LLMs) have exhibited outstanding performance in natural language processing tasks. However, these models remain susceptible to adversarial attacks in which slight input perturbations can lead to harmful or misleading outputs. A
Externí odkaz:
http://arxiv.org/abs/2412.13705
Graph Neural Networks (GNNs) perform effectively when training and testing graphs are drawn from the same distribution, but struggle to generalize well in the face of distribution shifts. To address this issue, existing mainstreaming graph rationaliz
Externí odkaz:
http://arxiv.org/abs/2412.12880
Seamless forecasting that produces warning information at continuum timescales based on only one system is a long-standing pursuit for weather-climate service. While the rapid advancement of deep learning has induced revolutionary changes in classica
Externí odkaz:
http://arxiv.org/abs/2411.10191
This paper presents a bimanual haptic display based on collaborative robot arms. We address the limitations of existing robot arm-based haptic displays by optimizing the setup configuration and implementing inertia/friction compensation techniques. T
Externí odkaz:
http://arxiv.org/abs/2411.07402
Autor:
Kim, Jiye, Kim, Minjun, Ji, Sooyeon, Min, Kyeongseon, Jeong, Hwihun, Shin, Hyeong-Geol, Oh, Chungseok, Straub, Sina, Kim, Seong-Gi, Lee, Jongho
A recently introduced quantitative susceptibility mapping (QSM) technique, $\chi$-separation, offers the capability to separate paramagnetic ($\chi_{\text{para}}$) and diamagnetic ($\chi_{\text{dia}}$) susceptibility distribution within the brain. In
Externí odkaz:
http://arxiv.org/abs/2410.12239
Autor:
Zhang, Hanlei, Bai, Jincheng, Chen, Xiabo, Li, Can, Zhong, Chuanjian, Fang, Jiye, Zhou, Guangwen
Scanning transmission electron microscopy (STEM) is a powerful tool to reveal the morphologies and structures of materials, thereby attracting intensive interests from the scientific and industrial communities. The outstanding spatial (atomic level)
Externí odkaz:
http://arxiv.org/abs/2409.16637
Autor:
Kim, Minjun, Ji, Sooyeon, Kim, Jiye, Min, Kyeongseon, Jeong, Hwihun, Youn, Jonghyo, Kim, Taechang, Jang, Jinhee, Bilgic, Berkin, Shin, Hyeong-Geol, Lee, Jongho
Magnetic susceptibility source separation ($\chi$-separation), an advanced quantitative susceptibility mapping (QSM) method, enables the separate estimation of para- and diamagnetic susceptibility source distributions in the brain. The method utilize
Externí odkaz:
http://arxiv.org/abs/2409.14030
In this paper, we study the $L^p$ maximal estimates for the Weyl sums $\sum_{n=1}^{N}e^{2\pi i(nx + n^{k}t)}$ with higher-order $k\ge3$ on $\mathbb{T}$, and obtain the positive and negative results. Especially for the case $k=3$, our result is sharp
Externí odkaz:
http://arxiv.org/abs/2408.15527
Publikováno v:
AMIA Joint Summits on Translational Science Proceedings, 2024, pp. 249-257
In the rapidly evolving field of healthcare, the integration of artificial intelligence (AI) has become a pivotal component in the automation of clinical workflows, ushering in a new era of efficiency and accuracy. This study focuses on the transform
Externí odkaz:
http://arxiv.org/abs/2406.07922