3 papers
cs.LG2026
Hardware-Friendly Input Expansion for Accelerating Function Approximation
Hu Lou, Yin-Jun Gao, Dong-Xiao Zhang +3
One-dimensional function approximation is a fundamental problem in scientific computing and engineering applications. While neural networks possess powerful universal approximation…
cs.LG2026
A Geometric Probe of the Accuracy-Robustness Trade-off: Sharp Boundaries in Symmetry-Breaking Dimensional Expansion
Yu Bai, Zhe Wang, Jiarui Zhang +3
The trade-off between clean accuracy and adversarial robustness is a pervasive phenomenon in deep learning, yet its geometric origin remains elusive. In this work, we utilize Symme…
eess.SY2024
Constructing and Evaluating Digital Twins: An Intelligent Framework for DT Development
Longfei Ma, Nan Cheng, Xiucheng Wang +4
The development of Digital Twins (DTs) represents a transformative advance for simulating and optimizing complex systems in a controlled digital space. Despite their potential, the…