2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2025
Guaranteeing Conservation of Integrals with Projection in Physics-Informed Neural Networks
Anthony Baez, Wang Zhang, Ziwen Ma +3
We propose a novel projection method that guarantees the conservation of integral quantities in Physics-Informed Neural Networks (PINNs). While the soft constraint that PINNs use t…
cs.LG2024★ 2 cited
Guaranteeing Conservation Laws with Projection in Physics-Informed Neural Networks
Anthony Baez, Wang Zhang, Ziwen Ma +3
Physics-informed neural networks (PINNs) incorporate physical laws into their training to efficiently solve partial differential equations (PDEs) with minimal data. However, PINNs…
cs.LG2023★ 1 cited
One step closer to unbiased aleatoric uncertainty estimation
Wang Zhang, Ziwen Ma, Subhro Das +4
Neural networks are powerful tools in various applications, and quantifying their uncertainty is crucial for reliable decision-making. In the deep learning field, the uncertainties…