EurekAlert!

Multi-objective evolutionary optimization for hardware-aware neural network pruning

Neural network pruning is a key technique for deploying artificial intelligence (AI) models based on deep neural networks (DNNs) on resource-constrained platforms, such as mobile devices. However, ...
pv magazine International

PV energy forecasting based on genetic algorithms, dynamic neural network

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
EurekAlert!

SEOULTECH researchers develop VFF-Net, a revolutionary alternative to backpropagation that transforms AI training

VFF-Net introduces three new methodologies: label-wise noise labelling (LWNL), cosine similarity-based contrastive loss (CSCL), and layer grouping (LG), addressing the challenges of applying a forward ...
Science Daily

Training algorithm breaks barriers to deep physical neural networks

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...
InfoWorld

The most popular neural network styles and how they work

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...
InfoWorld

Styles of machine learning: Intro to neural networks

Modeled on the human brain, neural networks are one of the most common styles of machine learning. Get started with the basic design and concepts of artificial neural networks. Artificial intelligence ...