Mar 16, 2023
A system integrating echo state graph neural networks and analogue random resistive memory arrays
Posted by Saúl Morales Rodriguéz in categories: biotech/medical, robotics/AI
Graph neural networks (GNNs) are promising machine learning architectures designed to analyze data that can be represented as graphs. These architectures achieved very promising results on a variety of real-world applications, including drug discovery, social network design, and recommender systems.
As graph-structured data can be highly complex, graph-based machine learning architectures should be designed carefully and effectively. In addition, these architectures should ideally be run on efficient hardware that support their computational demands without consuming too much power.