Physics-Informed Neural Networks (PINNs): Neural network models that integrate governing physical laws as constraints during training, enabling efficient solutions to differential equations.

To demonstrate the effectiveness of the approach, the researchers applied their physics-informed neural networks to model strike-slip faults, in which two blocks of the Earth’s crust move horizontally ...

The new approach uses an unsupervised neural network integrated with fluorescence microscopy priors within the deep-physics-informed sparsity framework to enhance resolution while preserving ...

National Renewable Energy Laboratory (NREL) researchers have developed and demonstrated a physics-informed neural network (PINN) model that can predict battery health nearly 1,000 times faster ...

Researchers have developed a transfer learning-enhanced physics-informed neural network (TLE-PINN) for predicting melt pool morphology in selective laser melting (SLM). This novel approach ...

With work on machine learning that uses artificial neural networks, John J. Hopfield and Geoffrey E. Hinton “showed a completely new way for us to use computers,” the committee said.