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Found 2 papers, 1 papers with code
Maximum-likelihood Estimators in Physics-Informed Neural Networks for High-dimensional Inverse Problems
Physics-informed neural networks (PINNs) have proven a suitable mathematical scaffold for solving inverse ordinary (ODE) and partial differential equations (PDE).
Kinetics-Informed Neural Networks
Chemical kinetics and reaction engineering consists of the phenomenological framework for the disentanglement of reaction mechanisms, optimization of reaction performance and the rational design of chemical processes.
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