Zobrazeno 1 - 10
of 1 837
pro vyhledávání: '"Li, Yijun"'
Autor:
Li, Yijun, Choi, Ki Sueng, Dunlop, Boadie W., Craighead, Wade Edward, Mayberg, Helen S., Garmire, Lana, Guo, Ying, Kang, Jian
Brain connectivity analysis is crucial for understanding brain structure and neurological function, shedding light on the mechanisms of mental illness. To study the association between individual brain connectivity networks and the clinical character
Externí odkaz:
http://arxiv.org/abs/2410.02965
Autor:
Li, Yuheng, Liu, Haotian, Cai, Mu, Li, Yijun, Shechtman, Eli, Lin, Zhe, Lee, Yong Jae, Singh, Krishna Kumar
In this paper, we introduce a model designed to improve the prediction of image-text alignment, targeting the challenge of compositional understanding in current visual-language models. Our approach focuses on generating high-quality training dataset
Externí odkaz:
http://arxiv.org/abs/2410.00905
Autor:
Shen, Guibao, Wang, Luozhou, Lin, Jiantao, Ge, Wenhang, Zhang, Chaozhe, Tao, Xin, Zhang, Yuan, Wan, Pengfei, Wang, Zhongyuan, Chen, Guangyong, Li, Yijun, Chen, Ying-Cong
Recent advancements in text-to-image generation have been propelled by the development of diffusion models and multi-modality learning. However, since text is typically represented sequentially in these models, it often falls short in providing accur
Externí odkaz:
http://arxiv.org/abs/2405.15321
Diffusion Models (DMs) have exhibited superior performance in generating high-quality and diverse images. However, this exceptional performance comes at the cost of expensive architectural design, particularly due to the attention module heavily used
Externí odkaz:
http://arxiv.org/abs/2405.05252
Autor:
Wang, Luozhou, Shen, Guibao, Liang, Yixun, Tao, Xin, Wan, Pengfei, Zhang, Di, Li, Yijun, Chen, Yingcong
In this research, we present a novel approach to motion customization in video generation, addressing the widespread gap in the thorough exploration of motion representation within video generative models. Recognizing the unique challenges posed by v
Externí odkaz:
http://arxiv.org/abs/2403.20193
Autor:
Xu, Minghui, Zhang, Jiahao, Guo, Hechuan, Cheng, Xiuzhen, Yu, Dongxiao, Hu, Qin, Li, Yijun, Wu, Yipu
Decentralized Storage Network (DSN) is an emerging technology that challenges traditional cloud-based storage systems by consolidating storage capacities from independent providers and coordinating to provide decentralized storage and retrieval servi
Externí odkaz:
http://arxiv.org/abs/2403.14985
The growing demand for personalized decision-making has led to a surge of interest in estimating the Conditional Average Treatment Effect (CATE). The intersection of machine learning and causal inference has yielded various effective CATE estimators.
Externí odkaz:
http://arxiv.org/abs/2402.18392
Autor:
Li, Yijun, Leung, Cheuk Hang, Sun, Xiangqian, Wang, Chaoqun, Huang, Yiyan, Yan, Xing, Wu, Qi, Wang, Dongdong, Huang, Zhixiang
Consumer credit services offered by e-commerce platforms provide customers with convenient loan access during shopping and have the potential to stimulate sales. To understand the causal impact of credit lines on spending, previous studies have emplo
Externí odkaz:
http://arxiv.org/abs/2312.10388
Despite recent significant strides achieved by diffusion-based Text-to-Image (T2I) models, current systems are still less capable of ensuring decent compositional generation aligned with text prompts, particularly for the multi-object generation. Thi
Externí odkaz:
http://arxiv.org/abs/2312.06712
The advent of predictive methodologies has catalyzed the emergence of data-driven decision support across various domains. However, developing models capable of effectively handling input time series data presents an enduring challenge. This study pr
Externí odkaz:
http://arxiv.org/abs/2309.12620