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VarunNair19 / Neural-Operators-1D-Physics

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A comparative analysis of DeepONet and FNO architectures, benchmarking their performance on Function-to-Function (Heat Equation) vs. Parameter-to-Function (Elastic Bar) PDE problems to motivate hybrid operator designs.

computational-physics pde-solver scientific-machine-learning fno physics-informed-neural-networks operator-learning deeponet neural-operators physics-informed-machine-learning hybrid-architectures benchmark-study
  • Updated Dec 4, 2025
  • Python

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