As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...

AI became powerful because of interacting mechanisms: neural networks, backpropagation and reinforcement learning, attention, ...

Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...

In 2025 Artprice successfully integrated all the key tools of its proprietary AI (Intuitive Artmarket®) into its internal ...

Representation learning lies at the core of modern artificial intelligence, enabling neural networks to uncover meaningful, ...