Traditional silicon-based architectures face challenges from rising AI demands, leading to a shift towards specialized computing solutions. Neuromorphic computing reduces power usage while enhancing ...

From hot-mic whispers of World Leaders to groundbreaking science, Prof. Mike Chan reveals why cellular regeneration — not organ swaps, holds the key to extending human healthspan and lifespan. A ...

This repository implements a Graph Neural Network (GNN) to predict patient length of stay using PyTorch Geometric. The implementation features advanced feature selection, interactive visualizations, ...

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.5c01525. Efficiency analysis of different normalization strategies ...

In modern drug discovery, generative molecular design models have greatly expanded the chemical space available to researchers, enabling rapid exploration of new compounds. Yet, a major challenge ...

Department of Chemistry and Biochemistry, University of Wisconsin─Eau Claire, Eau Claire, Wisconsin 54702, United States ...

1 Business College, California State University, Long Beach, CA, United States 2 School of Business and Management, Shanghai International Studies University, Shanghai, China In common graph neural ...

Proceedings of The Eighth Annual Conference on Machine Learning and Systems Graph neural networks (GNNs), an emerging class of machine learning models for graphs, have gained popularity for their ...

Abstract: Accurate molecular property prediction is of great importance for AI-based drug design and bioinformatics. Despite recent promising progress, existing methods face challenges due to ...