If Quantum Computing Is Solving “Impossible” Questions, How Do We Know They’re Right?

A new Swinburne study is addressing a core paradox: if quantum computing is solving problems that cannot be checked by conventional methods, how can we be certain the results are correct? Quantum ...

Explainable AI and turbulence: A fresh look at an unsolved physics problem

While atmospheric turbulence is a familiar culprit of rough flights, the chaotic movement of turbulent flows remains an ...
Scientific Research Publishing

Covariant-Scale: Riemannian Manifold Learning for Scale-Invariant Video Anomaly Detection ()

Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs when objects of different physical sizes appear identical in camera images ...
IEEE

GNNs' Generalization Improvement for Large-Scale Power System Analysis Based on Physics-Informed Self-Supervised Pre-Training

Abstract: Efficient and informative representation of system topologies is critical in AI-driven power system analysis (PSA). Despite a major breakthrough, recent approaches employing Graph Neural ...