Researchers have demonstrated a new training technique that significantly improves the accuracy of graph neural networks (GNNs)—AI systems used in applications from drug discovery to weather ...
The multiple condition (MC)-retention model is an uncertainty-aware graph-based neural network that predicts liquid chromatography (LC) retention times across multiple column chem ...
IEEE Spectrum on MSN
12 graphs that explain the state of AI in 2026
AI investment is skyrocketing while AI’s impact on jobs and public perception remains mixed ...
Scientists have developed a new method to measure ocean surface currents over large areas in greater detail than ever before. Called GOFLOW (Geostationary Ocean Flow), the approach applies deep ...
Abstract: The rise of graph-structured data has driven major advances in Graph Machine Learning (GML), where graph embeddings (GEs) map features from Knowledge Graphs (KGs) into vector spaces, ...
NEW YORK, April 8, 2026 /PRNewswire/ -- ACM, the Association for Computing Machinery, today named Matei Zaharia as the recipient of the ACM Prize in Computing for his visionary development of ...
Cyber threats are increasing in speed and complexity, driving the need for advanced detection techniques. Machine learning is ...
Online recommendation is moving into a new phase as transformers begin to reshape how graph-based systems understand users, items, and their hidden connections.
The increasing complexity of modern chemical engineering processes presents significant challenges for timely and accurate anomaly detection. Traditional ...
The number of scientific papers is growing so rapidly that scientists are no longer able to keep track of all of them, even ...
Abstract: Graph Machine Learning (Graph ML) has witnessed substantial advancements in recent years. With their remarkable ability to process graph-structured data, Graph ML techniques have been ...
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