Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

The functional characterization of different neuronal types has been a longstanding and crucial challenge. With the advent of physical quantum computers, it has become possible to apply quantum ...

The core tenet of the kernel method in machine learning is that it allows one to apply linear statistical methods to datasets that are complex and nonlinear in nature. The kernel function K ...

Researchers have successfully demonstrated quantum speedup in kernel-based machine learning.

Are two sets of data genuinely different, or is it because of randomness? This question, known as the two-sample testing ...