Understand how Highway Networks work and why they matter for training deep neural networks. A clear, beginner-friendly guide ...

Brain-inspired chips can slash AI energy use by as much as 100-fold, but the road to mainstream deployment is far from ...

CRISPR construct to genetically ablate the GABA transporter GAT3 in the mouse visual cortex, with effects on population-level neuronal activity. This work is important, as it sheds light on how GAT3 ...

MicroCloud Hologram Inc. announces a noise-resistant Deep Quantum Neural Network architecture, advancing quantum computing and machine learning efficiency.

Neural networks are the topic of this paper. Neural networks are very powerful as nonlinear signal processors, but obtained results are often far from satisfactory. The purpose of this article is to ...

Performance analysis of artificial intelligence–driven convolutional neural network architectures for liver tumor segmentation.

Energy and memory: A new neural network paradigm A dynamic energy landscape is at the heart of theorists' new model of memory retrieval Date: May 14, 2025 Source: University of California - Santa ...

In 1982 physicist John Hopfield translated this theoretical neuroscience concept into the artificial intelligence realm, with the formulation of the Hopfield network. In doing so, not only did he ...

Machine learning has emerged as a promising approach for predicting molecular properties of proteins, as it addresses limitations of experimental and traditional computational methods. Here, we ...

The data, totaling a staggering 1.6 petabytes, encompasses the electrical activity of over 200,000 cells, 2.5 miles (four kilometers) of branching axons, and more than 500 million synaptic connections ...

The wiring diagram also lacks information about timescales of neural dynamics or the role of neuromodulators or other molecular details that may influence the strength or function of various ...