Recent advances at the intersection of neural networks and inverse scattering problems have transformed traditional approaches to imaging and material characterisation. Inverse scattering involves ...

Even networks long considered "untrainable" can learn effectively with a bit of a helping hand. Researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have shown that a ...

A new technical paper titled “Hardware Acceleration for Neural Networks: A Comprehensive Survey” was published by researchers ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...

In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...

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