(A) Illustration of a convolutional neural network (NN) whose variational parameters (T) are encoded in the automatically differentiable tensor network (ADTN) shown in (B). The ADTN contains many ...

Deep machine learning has achieved remarkable success in various fields of artificial intelligence, but achieving both high interpretability and high efficiency simultaneously remains a critical ...

The quantum many body problem has been at the heart of much of theoretical and experimental physics over the past few decades. Even though we have understood the fundamental laws that govern the ...

Artificial intelligence (AI) has made tremendous progress since its inception, and neural networks are usually part of that advancement. Neural networks that apply weights to variables in AI models ...

Researchers from The University of New Mexico and Los Alamos National Laboratory have developed a novel computational framework that addresses a longstanding challenge in statistical physics.