Zobrazeno 1 - 10
of 1 281
pro vyhledávání: '"Zhang, Siwei"'
Autor:
Stevenson, Ian, Singh, Shayamal, Elkamshishy, Ahmed, Bigagli, Niccoló, Yuan, Weijun, Zhang, Siwei, Greene, Chris H., Will, Sebastian
A combined experimental and theoretical study is carried out on the three-body recombination process in a gas of microwave-shielded polar molecules. For ground-state polar molecules dressed with a strong microwave field, field-linked bound states can
Externí odkaz:
http://arxiv.org/abs/2407.04901
Autor:
Zhang, Siwei, Yuan, Weijun, Bigagli, Niccolò, Warner, Claire, Stevenson, Ian, Will, Sebastian
We report on the optical polarizability of microwave-shielded ultracold NaCs molecules in an optical dipole trap. While dressing a pair of rotational states with a microwave field, we observe a marked dependence of the optical polarizability on the i
Externí odkaz:
http://arxiv.org/abs/2406.19308
Autor:
Zhang, Siwei, Chen, Xi, Xiong, Yun, Wu, Xixi, Zhang, Yao, Fu, Yongrui, Zhao, Yinglong, Zhang, Jiawei
Temporal Graph Networks (TGNs) have demonstrated their remarkable performance in modeling temporal interaction graphs. These works can generate temporal node representations by encoding the surrounding neighborhoods for the target node. However, an i
Externí odkaz:
http://arxiv.org/abs/2406.11891
Autor:
Chen, Xi, Zhang, Siwei, Xiong, Yun, Wu, Xixi, Zhang, Jiawei, Sun, Xiangguo, Zhang, Yao, Zhao, Feng, Kang, Yulin
Temporal Interaction Graphs (TIGs) are widely utilized to represent real-world systems. To facilitate representation learning on TIGs, researchers have proposed a series of TIG models. However, these models are still facing two tough gaps between the
Externí odkaz:
http://arxiv.org/abs/2402.06326
Autor:
Li, Gen, Zhao, Kaifeng, Zhang, Siwei, Lyu, Xiaozhong, Dusmanu, Mihai, Zhang, Yan, Pollefeys, Marc, Tang, Siyu
Understanding the world in first-person view is fundamental in Augmented Reality (AR). This immersive perspective brings dramatic visual changes and unique challenges compared to third-person views. Synthetic data has empowered third-person-view visi
Externí odkaz:
http://arxiv.org/abs/2401.08739
Autor:
Zhang, Siwei, Bhatnagar, Bharat Lal, Xu, Yuanlu, Winkler, Alexander, Kadlecek, Petr, Tang, Siyu, Bogo, Federica
We propose RoHM, an approach for robust 3D human motion reconstruction from monocular RGB(-D) videos in the presence of noise and occlusions. Most previous approaches either train neural networks to directly regress motion in 3D or learn data-driven
Externí odkaz:
http://arxiv.org/abs/2401.08570
Autor:
Bigagli, Niccolò, Yuan, Weijun, Zhang, Siwei, Bulatovic, Boris, Karman, Tijs, Stevenson, Ian, Will, Sebastian
Publikováno v:
Nature 631, 289-293 (2024)
Ensembles of particles governed by quantum mechanical laws exhibit fascinating emergent behavior. Atomic quantum gases, liquid helium, and electrons in quantum materials all show distinct properties due to their composition and interactions. Quantum
Externí odkaz:
http://arxiv.org/abs/2312.10965
Autor:
Lee, Young-Hee, Zhu, Chen, Wiedemann, Thomas, Staudinger, Emanuel, Zhang, Siwei, Günther, Christoph
A swarm of robots has advantages over a single robot, since it can explore larger areas much faster and is more robust to single-point failures. Accurate relative positioning is necessary to successfully carry out a collaborative mission without coll
Externí odkaz:
http://arxiv.org/abs/2311.12580
Temporal Graph Networks (TGNs) have shown remarkable performance in learning representation for continuous-time dynamic graphs. However, real-world dynamic graphs typically contain diverse and intricate noise. Noise can significantly degrade the qual
Externí odkaz:
http://arxiv.org/abs/2309.02025
Continuous-time dynamic graph modeling is a crucial task for many real-world applications, such as financial risk management and fraud detection. Though existing dynamic graph modeling methods have achieved satisfactory results, they still suffer fro
Externí odkaz:
http://arxiv.org/abs/2309.02012