In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of two-dimensional memories, systems that can reliably store information despite ...
As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
Neural networks have revolutionised the landscape of machine learning, yielding unprecedented performance in complex tasks ranging from image recognition to natural language processing. At the heart ...
As the world grapples with the energy crisis and environmental concerns, the focus on renewable energy sources has intensified. Lithium-ion batteries, with their high energy density and low pollution, ...
Extreme Learning Machines (ELMs) represent a class of feedforward neural networks distinguished by their rapid learning speed and analytical determination of output weights. Unlike conventional neural ...
Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...
RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.
As artificial intelligence explodes in popularity, two of its pioneers have nabbed the 2024 Nobel Prize in physics. The prize surprised many, as these developments are typically associated with ...
Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...
SANTA CLARA, CA - February 05, 2026 - - Interview Kickstart today announced the launch of its Advanced Machine Learning Program, a specialized interview preparation track designed for engineers and ...