A new framework for generative diffusion models was developed by researchers at Science Tokyo, significantly improving generative AI models. The method reinterpreted Schrödinger bridge models as ...

Johns Hopkins and other BRAIN Initiative Cell Atlas Network (BICAN) researchers have enhanced a cellular road map of how the ...

Brain-inspired AI-hardware mimics neural efficiency to cut energy use, enabling autonomous devices to navigate, adapt and make real-time decisions independently.

Chinese researchers have published a new AI-driven system designed to interpret scramjet combustion simulations at speeds ...

This study presents a machine learning framework to predict the crashworthiness of multi-cell tubes. Five distinct cross-sectional designs are selected, and various structural configurations are ...

The spatio-temporal evolution of wall-bounded turbulence is characterized by high nonlinearity, multi-scale dynamics, and ...

Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require. When you purchase through links on our site, we may earn an affiliate ...

A command-line tool for aligning flow cytometry batches using autoencoder neural networks and generating voxel occupancy analysis. This tool processes FCS files to correct for batch effects, then ...

Abstract: Conventional energy-based methods struggle to determine the origin of Forced Oscillations (FOs) in renewable-rich systems because of their dependency on Dissipating Energy Flow (DEF) ...

The electrical grid is a crucial, sometimes fragile, piece of infrastructure. As connectivity to the grid increases, so too does its vulnerability. Public Service Company of New Mexico, the state’s ...

Researchers at Sandia National Laboratories have developed AI algorithms to detect physical problems, cyberattacks and both at the same time within the grid. “As more disturbances occur, whether from ...