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Soft-GNN: towards robust graph neural networks via self-adaptive data utilization

Graph neural networks (GNNs) have gained traction and have been applied to various graph-based data analysis tasks due to their high performance. However, a major concern is their robustness, ...
Bloomberg L.P.

Supply chain momentum strategies with graph neural networks

Supply chain data has been studied as a potential source of investment opportunity for years. Many possible theoretical approaches can be employed when considering how an investor could leverage ...
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 ...
Semiconductor Engineering

GNN-Based Framework for Hardware Trojan Detection, Including RISC-V Cores

A new technical paper titled “TROJAN-GUARD: Hardware Trojans Detection Using GNN in RTL Designs” was published by researchers at University of Connecticut and University of Minnesota. “hip ...