Unveiling schizophrenia's neural and mental signatures with machine learning

Schizophrenia is a severe and often highly debilitating psychiatric disorder characterized by distorted emotions, thinking patterns and altered perceptions of reality, as well as mental impairments.
Tech Xplore

New light-emitting artificial neurons could run AI systems more reliably

Over the past decades, computer scientists have developed increasingly advanced artificial intelligence (AI) systems that ...
Tech Xplore

New graph attention network models higher-order relationships in complex graph data

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...
eLife

Predicting human decision-making across task conditions via individuality transfer

Encoding individual behavioral traits into a low-dimensional latent representation enables the accurate prediction of ...
IEEE

A hybrid optical neural network with diverse parameterized layers for multifunctional intelligent processing

Abstract: The rise of artificial intelligence (AI) has driven increasingly stringent requirements for computing speed and energy efficiency. Optical computing offers a promising alternative due to its ...
Scientific Research Publishing

Pedamonti, D. (2018) Comparison of Non-Linear Activation Functions for Deep Neural Networks on MNIST Classification Task. arXiv.

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...
ksn.com

MicroCloud Hologram Inc. Releases Hybrid Quantum-Classical Convolutional Neural Network, Achieving New Breakthrough in MNIST Multi-Class Classification

SHENZHEN, China, Oct. 24, 2025 (GLOBE NEWSWIRE) -- MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a Quantum Convolutional Neural Network ...