近日，中国科学院昆明植物研究所陈纪军研究团队开发了基于深度学习的计算模型：ACAP-AG，旨在预测具有抗肝癌活性的天然候选分子。相关研究成果ACAP-AG: A graph neural network model for anticancer activity prediction by integrating heterogeneous ...

Announcing a new publication for Acta Materia Medica journal. Traditional Chinese medicine has shown therapeutic potential in treating osteoarthritis (OA) by regulating inflammation and maintaining ...

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 ...

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, ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...