arXiv (OAI Expanded)
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PhysSAE: Mechanistic Interpretability of PINNs with Sparse Autoencoders
Physics-Informed Neural Networks (PINNs) embed PDE residuals into neural network training, but their internal representations remain opaque: it is unknown what physical features their hidden layers encode or whether those features have a localized causal role. We present PhysSAE, a mechanistic inter
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