BSc Data Science vs BTech in Artificial Intelligence: Which tech degree should you choose today?

With technology growing faster than ever, many Class 12 students dream of working in IT, AI, or data-driven fields. Data is ...
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
News-Medical.Net

MEA-driven graph modeling identifies early connectivity changes linked to autism

Multi-electrode arrays (MEAs) provide a noninvasive interface with sub-millisecond temporal resolution and long-term, ...
Frontiers

DGAT: a dynamic graph attention neural network framework for EEG emotion recognition

Introduction: Emotion recognition based on electroencephalogram (EEG) signals has shown increasing application potential in fields such as brain-computer interfaces and affective computing. However, ...
IEEE

Visualization Method for Visual Analysis of Security Data Using Neural Networks

Abstract: The aim of this study is to develop a method for creating effective visualization models that can generate graphs from security data for later visual analysis using artificial intelligence ...
Scientific Research Publishing

Hamilton, W.L. (2020) Graph Representation Learning. Morgan & Claypool Publishers.

ABSTRACT: Knowledge Graph (KG) and neural network (NN) based Question-answering (QA) systems have evolved into the realm of intelligent information retrieval as they have been able to reach a high ...
Quanta Magazine

New Proof Settles Decades-Old Bet About Connected Networks

According to mathematical legend, Peter Sarnak and Noga Alon made a bet about optimal graphs in the late 1980s. They’ve now both been proved wrong. It started with a bet. In the late 1980s, at a ...
Frontiers

Recognition of brain activities via graph-based long short-term memory-convolutional neural network

1 School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China 2 College of Medical Imaging, Jiading District Central Hospital Affiliated Shanghai ...
IEEE

Neural Network Interpretability with Layer-Wise Relevance Propagation: Novel Techniques for Neuron Selection and Visualization

Abstract: Interpreting complex neural networks is crucial for understanding their decision-making processes, particularly in applications where transparency and accountability are essential. This ...