Zobrazeno 1 - 10
of 5 572
pro vyhledávání: '"ZHU, Xi"'
Autor:
Zheng, Xinyuan, Ravid, Orren, Barry, Robert A. J., Kim, Yoojean, Wang, Qian, Kim, Young-geun, Zhu, Xi, He, Xiaofu
Autism spectrum disorders (ASDs) are developmental conditions characterized by restricted interests and difficulties in communication. The complexity of ASD has resulted in a deficiency of objective diagnostic biomarkers. Deep learning methods have g
Externí odkaz:
http://arxiv.org/abs/2410.00068
Topological orders in 2+1d are spontaneous symmetry-breaking (SSB) phases of 1-form symmetries in pure states. The notion of symmetry is further enriched in the context of mixed states, where a symmetry can be either ``strong" or ``weak". In this wor
Externí odkaz:
http://arxiv.org/abs/2409.17530
Gapped fracton phases constitute a new class of quantum states of matter which connects to topological orders but does not fit easily into existing paradigms. They host unconventional features such as sub-extensive and robust ground state degeneracie
Externí odkaz:
http://arxiv.org/abs/2409.18206
When Diffusion MRI Meets Diffusion Model: A Novel Deep Generative Model for Diffusion MRI Generation
Diffusion MRI (dMRI) is an advanced imaging technique characterizing tissue microstructure and white matter structural connectivity of the human brain. The demand for high-quality dMRI data is growing, driven by the need for better resolution and imp
Externí odkaz:
http://arxiv.org/abs/2408.12897
In this work we are going to establish H\"older continuity of harmonic maps from an open set $\Omega$ in an ${\rm RCD}(K,N)$ space valued into a ${\rm CAT}(\kappa)$ space, with the constraint that the image of $\Omega$ via the map is contained in a s
Externí odkaz:
http://arxiv.org/abs/2408.00479
Autor:
Lin, Fake, Zhao, Ziwei, Zhu, Xi, Zhang, Da, Shen, Shitian, Li, Xueying, Xu, Tong, Zhang, Suojuan, Chen, Enhong
Last year has witnessed the re-flourishment of tag-aware recommender systems supported by the LLM-enriched tags. Unfortunately, though large efforts have been made, current solutions may fail to describe the diversity and uncertainty inherent in user
Externí odkaz:
http://arxiv.org/abs/2406.12020
Square lattice Hubbard models with tunable hopping ratio $t'/t$ are highly promising for realizing a variety of quantum phases and for shedding light on key puzzles in correlated quantum materials, including higher-temperature superconductivity. We s
Externí odkaz:
http://arxiv.org/abs/2406.02448
Autor:
Zhu, Yinghao, Ren, Changyu, Wang, Zixiang, Zheng, Xiaochen, Xie, Shiyun, Feng, Junlan, Zhu, Xi, Li, Zhoujun, Ma, Liantao, Pan, Chengwei
The integration of multimodal Electronic Health Records (EHR) data has notably advanced clinical predictive capabilities. However, current models that utilize clinical notes and multivariate time-series EHR data often lack the necessary medical conte
Externí odkaz:
http://arxiv.org/abs/2406.00036
Federated learning (FL), as an emerging collaborative learning paradigm, has garnered significant attention due to its capacity to preserve privacy within distributed learning systems. In these systems, clients collaboratively train a unified neural
Externí odkaz:
http://arxiv.org/abs/2405.17522
Autor:
Lin, Fake, Zhu, Xi, Zhao, Ziwei, Huang, Deqiang, Yu, Yu, Li, Xueying, Zheng, Zhi, Xu, Tong, Chen, Enhong
Recent years have witnessed the prosperity of knowledge graph based recommendation system (KGRS), which enriches the representation of users, items, and entities by structural knowledge with striking improvement. Nevertheless, its unaffordable comput
Externí odkaz:
http://arxiv.org/abs/2405.11531