The Nobel Prize in Physics was awarded to two scientists for discoveries that laid the groundwork for the artificial intelligence. British-Canadian Geoffrey Hinton, known as a 'godfather of AI', and ...
In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...
Using lab-grown brain tissue, researchers uncovered complex patterns of neural signaling that differ subtly between healthy ...
Don’t know your convolutional neural networks from your boosted decision trees? Symmetry is here to help. It’s time for some deep learning. Check out this list to pick up some new terminology—and ...
Overview: Clear problem definitions prevent wasted effort and keep machine learning work focused.Clean, well-understood data ...
AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...
A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...
A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an interpretable artificial intelligence (AI) framework named Convolutional Kolmogorov ...
The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...
Machine learning and deep learning are both parts of artificial intelligence, but they work in different ways — like a smart student versus a super-specialised ...
Results that may be inaccessible to you are currently showing.
Hide inaccessible results
Feedback