Generative AI can augment chemometrics by automating curation, connecting analytical outputs to textual knowledge, and ...
Researchers have proposed a Fourier graph neural network for estimating the state of health of lithium-ion batteries while ...
Researchers have demonstrated a new training technique that significantly improves the accuracy of graph neural networks ...
NeurIPS NeurIPS, or Neural Information Processing Systems, is pretty much the biggest gathering for anyone serious ...
Abstract: Recent years have witnessed fast developments of graph neural networks (GNNs) that have benefited myriad graph analytic tasks and applications. Most GNNs rely on the homophily assumption ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Graph neural networks (GNNs) have emerged as a powerful tool in predicting molecular ...
Detecting anomalies and threats in computer networks has been a center of cyber-security research for quite some time [1] and gaining popularity as new attack and defense techniques were made possible ...
Electrostatic interactions are fundamental to the structure, dynamics, and function of biomolecules, with broad applications in protein–ligand binding, enzymatic catalysis, and nucleic acid regulation ...