Zobrazeno 1 - 10
of 11 995
pro vyhledávání: '"An, RunZe"'
Autor:
Zhang, Runze
In this paper, we prove a $\partial\bar{\partial}$-type lemma on compact K\"ahler manifolds for logarithmic differential forms valued in the dual of a certain pseudo-effective line bundle, thereby confirming a conjecture proposed by X. Wan. We then d
Externí odkaz:
http://arxiv.org/abs/2412.09447
Autor:
Mijit, Emin, Ma, Peiyue, Sahle, Christoph J., Rosa, Angelika D., Hu, Zhiwei, De Angelis, Francesco, Lopez, Alberto, Amatori, Simone, Tchoudinov, Georghii, Joly, Yves, Irifune, Tetsuo, Rodrigues, Joao Elias F. S., Garbarino, Gaston, Parra, Samuel Gallego, Wang, Meng, Yu, Runze, Mathon, Olivier
The recent discovery of superconductivity in $\rm La_3Ni_2O_7$ has attracted significant attention due to its high critical temperature and analogy to cuprate oxides. The oxidation and spin states of Ni ions are among the most important local propert
Externí odkaz:
http://arxiv.org/abs/2412.08269
Deep supervised hashing has become a pivotal technique in large-scale image retrieval, offering significant benefits in terms of storage and search efficiency. However, existing deep supervised hashing models predominantly focus on generating fixed-l
Externí odkaz:
http://arxiv.org/abs/2412.08922
This paper studies the convergence rates of optimal transport (OT) map estimators, a topic of growing interest in statistics, machine learning, and various scientific fields. Despite recent advancements, existing results rely on regularity assumption
Externí odkaz:
http://arxiv.org/abs/2412.08064
This paper addresses hypothesis testing for the mean of matrix-valued data in high-dimensional settings. We investigate the minimum discrepancy test, originally proposed by Cragg (1997), which serves as a rank test for lower-dimensional matrices. We
Externí odkaz:
http://arxiv.org/abs/2412.07987
In this paper, we focus on the Ego-Exo Object Correspondence task, an emerging challenge in the field of computer vision that aims to map objects across ego-centric and exo-centric views. We introduce ObjectRelator, a novel method designed to tackle
Externí odkaz:
http://arxiv.org/abs/2411.19083
Root mean square propagation (abbreviated as RMSProp) is a first-order stochastic algorithm used in machine learning widely. In this paper, a stable gradient-adjusted RMSProp (abbreviated as SGA-RMSProp) with mini-batch stochastic gradient is propose
Externí odkaz:
http://arxiv.org/abs/2411.15877
Improving the ability to predict protein function can potentially facilitate research in the fields of drug discovery and precision medicine. Technically, the properties of proteins are directly or indirectly reflected in their sequence and structure
Externí odkaz:
http://arxiv.org/abs/2411.11366
Publikováno v:
Computer Graphics Forum (2024), 43: e15215
With the emergence of large-scale Text-to-Image(T2I) models and implicit 3D representations like Neural Radiance Fields (NeRF), many text-driven generative editing methods based on NeRF have appeared. However, the implicit encoding of geometric and t
Externí odkaz:
http://arxiv.org/abs/2411.10033
Autor:
Wang, Yongdong, Xiao, Runze, Kasahara, Jun Younes Louhi, Yajima, Ryosuke, Nagatani, Keiji, Yamashita, Atsushi, Asama, Hajime
Large Language Models (LLMs) have demonstrated significant reasoning capabilities in robotic systems. However, their deployment in multi-robot systems remains fragmented and struggles to handle complex task dependencies and parallel execution. This s
Externí odkaz:
http://arxiv.org/abs/2411.09022