Zobrazeno 1 - 10
of 2 502
pro vyhledávání: '"FENG, Shuo"'
Autor:
Chang, Zekun, Noma, Yuta, Feng, Shuo, Yang, Xinyi, Shinoda, Kazuhiro, Ta, Tung D., Yatani, Koji, Yokota, Tomoyuki, Someya, Takao, Kawahara, Yoshihiro, Narumi, Koya, Guimbretiere, Francois, Roumen, Thijs
OriStitch is a computational fabrication workflow to turn existing flat fabrics into self-folding 3D structures. Users turn fabrics into self-folding sheets by machine embroidering functional threads in specific patterns on fabrics, and then apply he
Externí odkaz:
http://arxiv.org/abs/2412.02891
To guarantee the safety and reliability of autonomous vehicle (AV) systems, corner cases play a crucial role in exploring the system's behavior under rare and challenging conditions within simulation environments. However, current approaches often fa
Externí odkaz:
http://arxiv.org/abs/2412.00243
Wire bending is a technique used in manufacturing to mass-produce items such as clips, mounts, and braces. Wire bending machines like the DIWire by Pensalabs have made this process accessible for personal fabrication. However, such machines are contr
Externí odkaz:
http://arxiv.org/abs/2410.23540
Designers of physical objects make assumptions on the material and fabrication workflow early in the design process. Recovering from bad assumptions is hard, because the design and resulting CAD model are locked-in to those assumptions. We present CA
Externí odkaz:
http://arxiv.org/abs/2410.18299
Testing and evaluation are critical to the development and deployment of autonomous vehicles (AVs). Given the rarity of safety-critical events such as crashes, millions of tests are typically needed to accurately assess AV safety performance. Althoug
Externí odkaz:
http://arxiv.org/abs/2409.14369
The generation of corner cases has become increasingly crucial for efficiently testing autonomous vehicles prior to road deployment. However, existing methods struggle to accommodate diverse testing requirements and often lack the ability to generali
Externí odkaz:
http://arxiv.org/abs/2409.06450
Difference-in-differences (DiD) is the most popular observational causal inference method in health policy, employed to evaluate the real-world impact of policies and programs. To estimate treatment effects, DiD relies on the "parallel trends assumpt
Externí odkaz:
http://arxiv.org/abs/2408.04617
Autor:
Su, Nan1 (AUTHOR), Feng, Shuo1 (AUTHOR), Wang, Lei1 (AUTHOR) leiwang@pku.edu.cn, Wu, Yuanzhi2 (AUTHOR)
Publikováno v:
International Journal of Market Research. Nov2024, Vol. 66 Issue 6, p778-809. 32p.
Social media bot detection is increasingly crucial with the rise of social media platforms. Existing methods predominantly construct social networks as graph and utilize graph neural networks (GNNs) for bot detection. However, most of these methods f
Externí odkaz:
http://arxiv.org/abs/2405.10558
Intelligent systems are increasingly integral to our daily lives, yet rare safety-critical events present significant latent threats to their practical deployment. Addressing this challenge hinges on accurately predicting the probability of safety-cr
Externí odkaz:
http://arxiv.org/abs/2403.13869