This paper presents APOSTLE, an asynchronously parallel optimization method for sizing analog transistors using Deep Neural Network (DNN) learning. This work introduces several methods to minimize ...

Researchers in China have created a dataset of various PV faults and normalized it to accommodate different array sizes and typologies. After testing the new approach in combination with the 1D-CNN ...

Scientists in India have proposed using a multilayer neural network to find line-to-ground, line-to-line, and bypass diode faults in PV module strings. They tested the new approach on a 22.5 kW ...

Discover the 20 best neural network software. Learn about the features of each software and find the best one. Written by eWEEK content and product recommendations are editorially independent. We ...

Alina Karakanta, Jon Dehdari, Josef van Genabith, Neural machine translation for low-resource languages without parallel corpora, Machine Translation, Vol. 32, No. 1/2, NLP in Low-Resource Languages ...

It’s even more difficult to understand a deep neural network that’s crunching a system such as Earth’s climate, which consists of myriad moving parts. Still, the rewards are worth the work.

Ellen Campana, leader of enterprise AI at KPMG U.S., suggests that the ideal neural network architecture should be based on the data size, the problem to be solved and the available computing ...

BitReXe is a proposed Layer 2 architecture to build out multiple EVM's on top of Bitcoin that can run in parallel, accomplishing more scalable smart contract execution on a second layer.