We're moving into Day 3 of Nvidia GTC, the chip-making giant's biggest conference of the year. CEO Jensen Huang took the ...

The U.S. Department of Energy now has two major supercomputing systems aimed at accelerating fusion energy research through ...

The spatio-temporal evolution of wall-bounded turbulence is characterized by high nonlinearity, multi-scale dynamics, and chaotic nature, making its accurate prediction a significant challenge for ...

New paired studies from the University of Minnesota Twin Cities show that machine learning can improve the prediction of floods. The studies, published in Water Resources Research and the Proceedings ...

Advances in artificial intelligence (AI) are now opening new possibilities for faster and more accurate flood mapping, ...

The Neural Processors Market is scaling with the shift from cloud-dependent AI to edge AI and device-level intelligence. Growth is being reinforced by a practical performance logic: inference tasks ...

1 Department of Computer Science, Mountains of the Moon University, Fortportal, Uganda. 2 Department of Computer Science and Informatics, University of Nairobi, Nairobi, Kenya. 3 Department of ...

This repository contains the dataset for the paper "Predicting Software Vulnerability Trends with Multi-Recurrent Neural Networks: A Time Series Forecasting Approach", published in the Proceedings of ...

This study evaluates ensemble models for wind energy forecasting in southern Brazil, the country’s second-largest wind energy producer. Forecasting is essential due to complex wind patterns and the ...

While acquisition curves in human learning averaged at the group level display smooth, gradual changes in performance, individual learning curves across cognitive domains reveal sudden, discontinuous ...