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Author

Nikhil Muralidhar

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Jul 2026

LIGO-PINN: Learned Initialization via Gated Optimization to Alleviate Convergence Failures in Physics Informed Neural Networks

This work proposes a framework for Learned Initialization via Gated Layerwise Optimization (LIGO-PINN) to overcome PINN convergence failures and demonstrates that this methodology outperforms state-of-the-art methods designed to alleviate PINN failures.

N. P. Anurag, S. Adhikari, Taniya Kapoor et al. · 0 citations

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