53 citations · 62 across the 14 of their papers we have counts for
4 papers · 1 filter
Physics-Informed Neural Network with Squeeze-Excitation-like Attention
Yun-Fei Song, Long-Gang Pang, Fu-Peng Li +1
We introduce SEA-PINN, a novel architecture that incorporates a Squeeze-Excitation-like attention mechanism into physics-informed neural networks to dynamically recalibrate the imp…
Phase-space entropy at acquisition reflects downstream learnability
Xiu-Cheng Wang, Jun-Jie Zhanga, Nan Cheng +3
Modern learning systems work with data that vary widely across domains, but they all ultimately depend on how much structure is already present in the measurements before any model…
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…
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,…