Graph Neural Networks (GNN), a cutting-edge approach in artificial intelligence, can significantly improve computational calculations in heterogeneous catalysis. Researchers have made a groundbreaking ...

This article is part of our coverage of the latest in AI research. What is the next step toward bridging the gap between natural and artificial intelligence? Scientists and researchers are divided on ...

Self-supervised models generate implicit labels from unstructured data rather than relying on labeled datasets for supervisory signals. Self-supervised learning (SSL), a transformative subset of ...

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 ...

Giulia Livieri sets out remarkable new research with results that clarify how learning works on complex graphs and how quickly any method (including Graph Convolutional Networks) can learn from them, ...

Self-supervised learning allows a neural network to figure out for itself what matters. The process might be what makes our own brains so successful. For a decade now, many of the most impressive ...