62 citations
- University of Hong KongHK13 papers
- Guangzhou UniversityCN8 papers
- Hong Kong University of Science and TechnologyHK8 papers
- Chinese Academy of SciencesCN4 papers
- Oak Ridge National LaboratoryUS2 papers
- Shenzhen Institutes of Advanced TechnologyCN2 papers
- The University of TokyoJP2 papers
- University of Science and Technology of ChinaCN2 papers
- Argonne National LaboratoryUS1 paper
- Astronomy and SpaceAU1 paper
- Beijing Academy of Quantum Information SciencesCN1 paper
- Boston CollegeUS1 paper
20 papers
Knowledge-guided Disentanglement with Atomic Actions for Action Recognition
Tianci Wu, Siqi Cao, Guangming Zhu +6
Action recognition in complex scenes often involves multiple concurrent fine-grained actions, making it challenging to model internal action structures. Most existing methods rely…
Personalized Multi-Interest Modeling for Cross-Domain Recommendation to Cold-Start Users
Xiaodong Li, Jiawei Sheng, Jiangxia Cao +6
Cross-domain recommendation (CDR) has demonstrated to be an effective solution for alleviating the user cold-start issue. By leveraging rich user-item interactions available in a r…
Thin-Film-Engineered Self-Assembly of 3D Coaxial Microfluidics with a Tunable Polyimide Membrane for Bioelectronic Power
Aleksandr I. Egunov, Hongmei Tang, Pablo E. Saenz +11
Thin-film self-assembly of three-dimensional (3D) microsystems presents a compelling route to integrate complex functionalities into ultra-compact volumes, yet strategies for incor…
Magnons in multiorbital Hubbard models, from Lieb to kagome
Teng-Fei Ying, Hugo U. R. Strand, Benjamin T. Zhou +1
We investigate the magnetic orders and excitations in a half-filled Hubbard model that continuously interpolates between the Lieb and kagome lattices. Using self-consistent Hartree…
Bgolearn: a Unified Bayesian Optimization Framework for Accelerating Materials Discovery
Bin Cao, Jie Xiong, Jiaxuan Ma +11
Efficient exploration of vast compositional and processing spaces remains a major challenge in accelerated materials discovery. Bayesian optimization (BO) provides a principled app…
A Compact Dual-Beam Zeeman Slower for High-Flux Cold Atoms
Chen Chen, Kejun Liu, Dezhou Deng +6
We present a compact design of dual-beam Zeeman slower optimized for efficient production of cold atom applications. Traditional single-beam configurations face challenges from sub…