conflict-averse

New ModSync Framework Overcomes Capacity-Driven Failures in Physics-Informed Neural Networks

Researchers introduced a new framework called Modular-Sparsity Synchronization (ModSync) to address a failure mode in physics-informed neural networks (PINNs) where overparameterization leads to functional modularity. ModSync integrates structural optimization into conflict-averse training, preventing gradient interference and achieving state-of-the-art accuracy across diverse PDE benchmarks.