Security Boulevard

NDSS 2025 – Defending Against Backdoor Attacks On Graph Neural Networks Via Discrepancy Learning

Hao Yu (National University of Defense Technology), Chuan Ma (Chongqing University), Xinhang Wan (National University of Defense Technology), Jun Wang (National University of Defense Technology), Tao ...
Finextra

Graph Neural Networks and GraphRAG: Navigating Open-World Complexity in Finance

Graph Neural Networks (GNNs) and GraphRAG don’t “reason”—they navigate complex, open-world financial graphs with traceable, multi-hop evidence. Here’s why BFSI leaders should embrace graph-native AI ...
Frontiers

AI-Driven Complex Networks: Structure, Dynamics, and Intelligent Applications

In an increasingly interconnected world, understanding the behavior and structure of complex networks has become essential ...
Semiconductor Engineering

Physics Simulation With Graph Neural Networks Targeting Mobile

The demand for immersive, realistic graphics in mobile gaming and AR or VR is pushing the limits of mobile hardware. Achieving lifelike simulations of fluids, cloth, and other materials historically ...
EurekAlert!

Real-time, large-scale graph neural network inference through BingoCGN

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...
Semiconductor Engineering

Predicting Defect Properties In Semiconductors With Graph Neural Networks

A technical paper titled “Accelerating Defect Predictions in Semiconductors Using Graph Neural Networks” was published by researchers at Purdue University, Indian Institute of Technology (IIT) Madras, ...
EurekAlert!

Integrating physics and AI: Novel graph neural network models enhance precipitation forecasting

In the AI era, pure data-driven meteorological and climate models are gradually catching up with, and even surpassing, traditional numerical models. However, significant challenges persist in current ...