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

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 ...

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 ...

John Hopfield (left) and Geoffrey Hinton (right) won the 2024 Nobel Prize in physics for discoveries that allow machine learning with artificial neural networks.

John Hopfield and Geoffrey Hinton won the Nobel Prize in Physics for their work on artificial neural networks and machine learning. Jonathan Nackstrand / AFP via Getty Images A pair of scientists ...

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.