The rapid evolution of neural network methodologies has significantly improved the prediction of respiratory motion, which is critical for the precision of radiotherapy and robotic-assisted surgical ...

Calculations show that injecting randomness into a quantum neural network could help it determine properties of quantum ...

Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...

Physics-informed neural networks are faster and more accurate at predicting space junk trajectories than conventional methods, says Sierra Space. Credit: Alamy Stock Photo Sierra Space says it can ...

The demand for immersive, realistic graphics in mobile gaming and AR or VR is pushing the limits of mobile hardware. Achieving lifelike simulations of fluids, cloth, and other materials historically ...

In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture evolution, and energy efficiency under varying conditions. Drying remains one of ...

Researchers have developed a hybrid CFD-neural network model for predicting TAIs in hydrogen-fueled turbines, improving ...

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...