Tag: Bayesian uncertainty quantification

Researchers developed a physics-constrained neural network framework that analytically estimates magnetization vectors and maps subsurface targets with Bayesian uncertainty quantification.

Researchers have introduced NeuroQ-MGST, an integrated multimodal artificial intelligence framework combining spiking neural networks, dynamic graph transformers, and quantum-inspired variational ...