Latent-MoE: Domain-Aware Mixture-of-Experts for PDEs with Multi-Regime Physics
Latent-MoE adds domain-aware mixture-of-experts routing to PINNs, improving accuracy over an order of magnitude on multi-regime physics PDEs.
The paper shows standard coordinate networks used in physics-informed neural networks have translation-variant NTKs causing long-range gradient conflicts on PDEs with spatially varying physics. MoE architectures with centered compact-support routers produce a uniformly banded NTK that localizes learning. Latent-MoE interleaves domain-aware MoE blocks in a shared backbone, outperforming FB-PINNs and X-PINNs by over an order of magnitude on multi-stage time-variable physics benchmarks.
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