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 ...

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

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 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 ...

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 ...

Scientists suggested approaches of "strong" and "weak" prediction in order to prognose the behavior of stochastic, that means random systems, with the help of neural networks. Authors defined when it ...

The simplified approach makes it easier to see how neural networks produce the outputs they do. A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher.