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SVNIT Surat
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SPARC-Net achieves up to 100% error reduction in shock-dominated PDEs by tackling the multi-causal failures of traditional PINNs head-on.
A unified benchmark reveals the trade-offs between pixel-wise accuracy and perceptual realism in state-of-the-art image super-resolution techniques.
PINNs get a boost: adaptive loss balancing and residual-based collocation cuts errors by up to 70% in stiff PDEs.
