Brain-inspired chips can slash AI energy use by as much as 100-fold, but the road to mainstream deployment is far from guaranteed.

Using an advanced Monte Carlo method, Caltech researchers found a way to tame the infinite complexity of Feynman diagrams and ...

When implementing Artificial Neural Networks with imperative programing languages, the resulting programs are usually highly coupled. This problem usually hampers distribution over multiple processors ...

This paper presents a novel adaptive learning-rate backpropagation neural network (ALR-BPNN) algorithm based on the minimization of mean-square deviation (MSD) to implement a fast convergence rate and ...