Enforcing Physical Constraints in Neural Neural Networks through Differentiable PDE Layer

ICLR 2020 Chiyu "Max" JiangKarthik KashinathPrabhatPhilip Marcus

Recent studies at the intersection of physics and deep learning have illustrated successes in the application of deep neural networks to partially or fully replace costly physics simulations. Enforcing physical constraints to solutions generated by neural networks remains a challenge, yet it is essential to the accuracy and trustworthiness of such model predictions... (read more)

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