An international team led by Einstein Professor Cecilia Clementi in the Department of Physics at Freie Universität Berlin has ...

Tariffs are now feeding through to consumer prices, pushing inflation higher and disrupting the prior disinflationary trend.

When someone starts a new job, early training may involve shadowing a more experienced worker and observing what they do ...

Specifically, ICST-DNET consists of three parts, namely the Spatio-Temporal Causality Learning (STCL), Causal Graph Generation (CGG), and Speed Fluctuation Pattern Recognition (SFPR) modules.

Researchers have developed an innovative AI approach that embeds causal reasoning into offline reinforcement learning, enabling autonomous systems like driverless cars and medical support devices to ...

To address these challenges, we propose AffiGrapher, a physics-driven graph neural network that integrates a physics-informed graph architecture with contrastive learning. Incorporating multiple RNA ...

Recently, topological graphs based on structural or functional connectivity of brain network have been utilized to construct graph neural networks (GNN) for Electroencephalogram (EEG) emotion ...

Our results demonstrate that the proposed method significantly outperforms traditional machine learning and convolution neural network approaches, highlighting its effectiveness in large-scale ...