Gradient Surgery for Physics-Informed Neural Networks
ScientificML
This paper studies gradient conflicts and multi-task optimization in Physics-Informed Neural Networks, with implications for more stable convergence in stiff and high-frequency partial differential equations.
New See LICENSE file Physics-Informed Neural NetworksGradient ConflictsMulti-Task Optimization