Zobrazeno 1 - 10
of 375 061
pro vyhledávání: '"Ling, P"'
Autor:
Lin, Leah Ya-Ling, Hashimoto, Tetsuya, Goto, Tomotsugu, Raquel, Bjorn Jasper, Ho, Simon C. -C., Chen, Bo-Han, Kim, Seong Jin, Ling, Chih-Teng
Fast radio bursts (FRBs) are millisecond-duration radio waves from the Universe. Even though more than 50 physical models have been proposed, the origin and physical mechanism of FRB emissions are still unknown. The classification of FRBs is one of t
Externí odkaz:
http://arxiv.org/abs/2410.00576
Deep learning models have made remarkable strides in precipitation prediction, yet they continue to struggle with capturing the spatial details of the features of radar images, particularly over high precipitation intensity areas. This shortcoming is
Externí odkaz:
http://arxiv.org/abs/2410.14103
Autor:
Shimizu, Cogan, Stephe, Shirly, Barua, Adrita, Cai, Ling, Christou, Antrea, Currier, Kitty, Dalal, Abhilekha, Fisher, Colby K., Hitzler, Pascal, Janowicz, Krzysztof, Li, Wenwen, Liu, Zilong, Mahdavinejad, Mohammad Saeid, Mai, Gengchen, Rehberger, Dean, Schildhauer, Mark, Shi, Meilin, Norouzi, Sanaz Saki, Tian, Yuanyuan, Wang, Sizhe, Wang, Zhangyu, Zalewski, Joseph, Zhou, Lu, Zhu, Rui
KnowWhereGraph is one of the largest fully publicly available geospatial knowledge graphs. It includes data from 30 layers on natural hazards (e.g., hurricanes, wildfires), climate variables (e.g., air temperature, precipitation), soil properties, cr
Externí odkaz:
http://arxiv.org/abs/2410.13948
Stochastic approximation (SA) that involves multiple coupled sequences, known as multiple-sequence SA (MSSA), finds diverse applications in the fields of signal processing and machine learning. However, existing theoretical understandings {of} MSSA a
Externí odkaz:
http://arxiv.org/abs/2410.13743
Finding a mass formula for a given class of linear codes is a fundamental problem in combinatorics and coding theory. In this paper, we consider the action of the unitary (resp. symplectic) group on the set of all Hermitian (resp. symplectic) linear
Externí odkaz:
http://arxiv.org/abs/2410.13578
Autor:
Han, Wenhan, Fang, Meng, Zhang, Zihan, Yin, Yu, Song, Zirui, Chen, Ling, Pechenizkiy, Mykola, Chen, Qingyu
The integration of large language model (LLM) techniques in the field of medical analysis has brought about significant advancements, yet the scarcity of large, diverse, and well-annotated datasets remains a major challenge. Medical data and tasks, w
Externí odkaz:
http://arxiv.org/abs/2410.13458
Autor:
Li, ChaoRong, Ling, XuDong, Xue, YiLan, Luo, Wenjie, Zhu, LiHong, Qin, FengQing, Zhou, Yaodong, Huang, Yuanyuan
Short-term precipitation forecasting remains challenging due to the difficulty in capturing long-term spatiotemporal dependencies. Current deep learning methods fall short in establishing effective dependencies between conditions and forecast results
Externí odkaz:
http://arxiv.org/abs/2410.13314
We consider the spatially inhomogeneous Boltzmann equation without angular cutoff for soft potentials. For any given initial datum such that the mass, energy and entropy densities are bounded and the mass is away from vacuum, we establish the local-i
Externí odkaz:
http://arxiv.org/abs/2410.13205
Autor:
Chuang, Yun-Yen, Hsu, Hung-Min, Lin, Kevin, Gu, Chen-Sheng, Li, Ling Zhen, Chang, Ray-I, Lee, Hung-yi
The diffusion model, a new generative modeling paradigm, has achieved significant success in generating images, audio, video, and text. It has been adapted for sequence-to-sequence text generation (Seq2Seq) through DiffuSeq, termed S2S Diffusion. Exi
Externí odkaz:
http://arxiv.org/abs/2410.13201
Current neural audio codecs typically use residual vector quantization (RVQ) to discretize speech signals. However, they often experience codebook collapse, which reduces the effective codebook size and leads to suboptimal performance. To address thi
Externí odkaz:
http://arxiv.org/abs/2410.12359