This AI Model Can Intuit How the Physical World Works

Researchers have developed an AI system that learns about the world via videos and demonstrates a notion of “surprise” when ...
Tech Xplore

Overparameterized neural networks: Feature learning precedes overfitting, research finds

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...
Scientific Research Publishing

Marbel, R., Cohen, Y., Dubin, R., Dvir, A. and Hajaj, C. (2024) Cloudy with a Chance of Anomalies: Dynamic Graph Neural Network for Early Detection of Cloud Services’ User ...

ABSTRACT: Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex ...
C&EN

Enhanced Prediction of Absorption and Emission Wavelengths of Organic Compounds through Hybrid Graph Neural Network Architectures

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Despite these advancements, predicting absorption and emission ...
IEEE

GIGNet: A Graph-in-Graph Neural Network for Automatic Modulation Recognition

Abstract: In this paper, we propose a robust end-to-end classification model, Graph-in-Graph Neural Network (GIGNet), for automatic modulation recognition (AMR). In GIGNet, multi-level graph neural ...
GitHub

Subgraph-conditioned Graph Information Bottleneck

We aim to build a pre-trained Graph Neural Network (GNN) model on molecules without human annotations or prior knowledge. Although various attempts have been proposed to overcome limitations in ...
Frontiers

User recommendation method integrating hierarchical graph attention network with multimodal knowledge graph

1 Business College, California State University, Long Beach, CA, United States 2 School of Business and Management, Shanghai International Studies University, Shanghai, China In common graph neural ...
Frontiers

Explainable graph neural network based on metabolic brain imaging for differential diagnosis of parkinsonism

Background: Accurate differentiation of parkinsonian syndromes remains challenging due to overlapping clinical manifestations and subtle neuroimaging variations. This study introduces an explainable ...
Hosted on MSN

Graph Neural Network Can Detect Epileptogenic Focal Cortical Dysplasia

WEDNESDAY, March 19, 2025 (HealthDay News) -- A graph neural network using data from the Multicenter Epilepsy Lesion Detection (MELD) Project (MELD Graph) can detect epileptogenic focal cortical ...