Zobrazeno 1 - 10
of 792 460
pro vyhledávání: '"A, Wan"'
Autor:
Wan, Zishen, Liu, Che-Kai, Yang, Hanchen, Raj, Ritik, Li, Chaojian, You, Haoran, Fu, Yonggan, Wan, Cheng, Li, Sixu, Kim, Youbin, Samajdar, Ananda, Lin, Yingyan Celine, Ibrahim, Mohamed, Rabaey, Jan M., Krishna, Tushar, Raychowdhury, Arijit
The remarkable advancements in artificial intelligence (AI), primarily driven by deep neural networks, are facing challenges surrounding unsustainable computational trajectories, limited robustness, and a lack of explainability. To develop next-gener
Externí odkaz:
http://arxiv.org/abs/2409.13153
Autor:
Sun, Wan-Peng, Zhang, Ji-Guo, Li, Yichao, Hou, Wan-Ting, Zhang, Fu-Wen, Zhang, Jing-Fei, Zhang, Xin
Fast radio bursts (FRBs) are enigmatic high-energy events with unknown origins, which are observationally divided into two categories, i.e., repeaters and non-repeaters. However, there are potentially a number of non-repeaters that may be misclassifi
Externí odkaz:
http://arxiv.org/abs/2409.11173
In [DGLW], we use certain special elements and their commutation relations in the Hecke-Clifford algebras $H^c_{r,R}$ to derive some fundamental multiplication formulas associated with the natural bases in queer $q$-Schur superalgebras $Q_q(n,r;R)$ i
Externí odkaz:
http://arxiv.org/abs/2411.14764
Efficient management of storage resources in big data and cloud computing environments requires accurate identification of data's "cold" and "hot" states. Traditional methods, such as rule-based algorithms and early AI techniques, often struggle with
Externí odkaz:
http://arxiv.org/abs/2411.14759
Fast radio bursts (FRBs) are high-energy, short-duration phenomena in radio astronomy. Identifying their host galaxies can provide insights into their mysterious origins. In this paper, we introduce a novel approach to identifying potential host gala
Externí odkaz:
http://arxiv.org/abs/2411.13973
Realistic simulation of dynamic scenes requires accurately capturing diverse material properties and modeling complex object interactions grounded in physical principles. However, existing methods are constrained to basic material types with limited
Externí odkaz:
http://arxiv.org/abs/2411.14423
Autor:
Feng, Xidong, Wan, Ziyu, Fu, Haotian, Liu, Bo, Yang, Mengyue, Koushik, Girish A., Hu, Zhiyuan, Wen, Ying, Wang, Jun
Reinforcement Learning (RL) mathematically formulates decision-making with Markov Decision Process (MDP). With MDPs, researchers have achieved remarkable breakthroughs across various domains, including games, robotics, and language models. This paper
Externí odkaz:
http://arxiv.org/abs/2411.14251
Recent improvements in visual synthesis have significantly enhanced the depiction of generated human photos, which are pivotal due to their wide applicability and demand. Nonetheless, the existing text-to-image or text-to-video models often generate
Externí odkaz:
http://arxiv.org/abs/2411.14205
In order to solve the problem of insufficient generation quality caused by traditional patent text abstract generation models only originating from patent specifications, the problem of new terminology OOV caused by rapid patent updates, and the prob
Externí odkaz:
http://arxiv.org/abs/2411.14072
Autor:
Zhang, Hui, Yang, Chengran, Mok, Wai-Keong, Wan, Lingxiao, Cai, Hong, Li, Qiang, Gao, Feng, Luo, Xianshu, Lo, Guo-Qiang, Chin, Lip Ket, Shi, Yuzhi, Thompson, Jayne, Gu, Mile, Liu, Ai Qun
Integrated photonic circuits play a crucial role in implementing quantum information processing in the noisy intermediate-scale quantum (NISQ) era. Variational learning is a promising avenue that leverages classical optimization techniques to enhance
Externí odkaz:
http://arxiv.org/abs/2411.12417