Science Daily

AI just found 5 powerful materials that could replace lithium batteries

AI is helping scientists crack the code on next-gen batteries that could replace lithium-ion tech. By discovering novel porous materials, researchers may have paved the way for more powerful and ...
IEEE

GDiffMAE: Guided Diffusion Enhanced Mask Graph AutoEncoder for Recommendation

Abstract: Despite advancements using graph neural networks (GNNs) to capture complex user-item interactions, challenges persist due to data sparsity and noise. To address these, self-supervised ...
Frontiers

Subtyping insomnia disorder with a population graph attention autoencoder: revealing two distinct biotypes

Insomnia disorder (ID) is neurobiologically heterogeneous and often eludes characterization by traditional group-level neuroimaging. Subtyping based on neuroimaging and clinical data offers a ...
IEEE

AE-HRS: Autoencoder-Based Health Recommender System for Forecasting Cardiovascular Conditions through Collaborative Filtering

Abstract: Health Recommender Systems (HRS) are commonly used as medical tools to provide personalized recommendations based on clinical records data. This work proposes an HRS based on a matrix ...