Graph neural networks (GNNs) are specialised deep learning architectures designed to operate on data represented as graphs, where entities are modelled as nodes and relationships as edges. In ...
Graph neural networks have become essential for molecular property prediction in drug discovery and materials design. However, graph neural networks face a critical challenge called oversmoothing: ...
Stephane is a tech enthusiast and AI advocate with a deep-seated passion for leveraging technology to solve real-world problems. With a background in Chemistry and hands-on experience in AI,... We ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results