3 papers
cs.LG2025
On the uncertainty principle of neural networks
Jun-Jie Zhang, Dong-Xiao Zhang, Jian-Nan Chen +2
In this study, we explore the inherent trade-off between accuracy and robustness in neural networks, drawing an analogy to the uncertainty principle in quantum mechanics. We propos…
cs.LG2024
Is AI Robust Enough for Scientific Research?
Jun-Jie Zhang, Jiahao Song, Xiu-Cheng Wang +14
We uncover a phenomenon largely overlooked by the scientific community utilizing AI: neural networks exhibit high susceptibility to minute perturbations, resulting in significant d…
cs.LG2024
Symmetry Breaking in Neural Network Optimization: Insights from Input Dimension Expansion
Jun-Jie Zhang, Nan Cheng, Fu-Peng Li +4
Understanding the mechanisms behind neural network optimization is crucial for improving network design and performance. While various optimization techniques have been developed,…