Multi-sample \(\zeta \)-mixup: richer, more realistic synthetic samples from a p-series interpolant

Modern deep learning training procedures rely on model regularization techniques such as data augmentation methods, which generate training samples that increase the diversity of data and richness of label inf...

Small molecule autoencoders: architecture engineering to optimize latent space utility and sustainability

Autoencoders are frequently used to embed molecules for training of downstream deep learning models. However, evaluation of the chemical information quality in the latent spaces is lacking and the model archit...

Higher-order structures of local collaboration networks are associated with individual scientific productivity

The prevalence of teamwork in contemporary science has raised new questions about collaboration networks and the potential impact on research outcomes. Previous studies primarily focused on pairwise interactio...