Zobrazeno 1 - 10
of 9 453
pro vyhledávání: '"Weizhi An"'
Publikováno v:
BioMedInformatics, Vol 4, Iss 2, Pp 1556-1571 (2024)
Acquiring meaningful representations of gene expression is essential for the accurate prediction of downstream regulatory tasks, such as identifying promoters and transcription factor binding sites. However, the current dependency on supervised learn
Externí odkaz:
https://doaj.org/article/5a108b4ad4014218a7e3e0c7d67365ff
Autor:
Chen, Siyuan, Zhao, Shihan, Xiong, Weizhi, Tian, Ye, Jiang, Hui, Ling, Jiacheng, Wang, Shishe, Tang, Jian
The Muonium-to-Antimuonium Conversion Experiment (MACE) is proposed to search for charged lepton flavor violation and increase the sensitivity by three orders of magnitude compared to the PSI experiment in the 1990s. A clear signature of this convers
Externí odkaz:
http://arxiv.org/abs/2408.17114
Spiking neural networks (SNNs) are becoming a promising alternative to conventional artificial neural networks (ANNs) due to their rich neural dynamics and the implementation of energy-efficient neuromorphic chips. However, the non-differential binar
Externí odkaz:
http://arxiv.org/abs/2408.09403
Audio-driven talking face video generation has attracted increasing attention due to its huge industrial potential. Some previous methods focus on learning a direct mapping from audio to visual content. Despite progress, they often struggle with the
Externí odkaz:
http://arxiv.org/abs/2408.05416
Audio-driven lip sync has recently drawn significant attention due to its widespread application in the multimedia domain. Individuals exhibit distinct lip shapes when speaking the same utterance, attributed to the unique speaking styles of individua
Externí odkaz:
http://arxiv.org/abs/2408.05412
Autor:
Zhang, Zhenghao, Liao, Junchao, Li, Menghao, Dai, Zuozhuo, Qiu, Bingxue, Zhu, Siyu, Qin, Long, Wang, Weizhi
Recent advancements in Diffusion Transformer (DiT) have demonstrated remarkable proficiency in producing high-quality video content. Nonetheless, the potential of transformer-based diffusion models for effectively generating videos with controllable
Externí odkaz:
http://arxiv.org/abs/2407.21705
Autor:
Zhang, Weizhi, Yang, Liangwei, Song, Zihe, Zou, Henry Peng, Xu, Ke, Fang, Liancheng, Yu, Philip S.
The efficiency and scalability of graph convolution networks (GCNs) in training recommender systems (RecSys) have been persistent concerns, hindering their deployment in real-world applications. This paper presents a critical examination of the neces
Externí odkaz:
http://arxiv.org/abs/2407.18910
We present PartGLEE, a part-level foundation model for locating and identifying both objects and parts in images. Through a unified framework, PartGLEE accomplishes detection, segmentation, and grounding of instances at any granularity in the open wo
Externí odkaz:
http://arxiv.org/abs/2407.16696
Solid-water interfaces are crucial to many physical and chemical processes and are extensively studied using surface-specific sum-frequency generation (SFG) spectroscopy. To establish clear correlations between specific spectral signatures and distin
Externí odkaz:
http://arxiv.org/abs/2407.15338
Dataset distillation offers a lightweight synthetic dataset for fast network training with promising test accuracy. To imitate the performance of the original dataset, most approaches employ bi-level optimization and the distillation space relies on
Externí odkaz:
http://arxiv.org/abs/2407.15138