Meanwhile, Sparconv-VAE is the first variational autoencoder built entirely using sparse convolutional networks. This ensures that the encoding and decoding processes remain consistent in modality, ...

For the past six years, Los Alamos National Laboratory has led the world in trying to understand one of the most frustrating barriers that faces variational quantum computing: the barren plateau.

A transfer-learned hierarchical variational autoencoder model for computational design of anticancer peptides.. If you have the appropriate software installed, you can download article citation data ...

In this work, we developed a generative model for the inverse design of transition metal ligands and complexes, based on the junction tree variational autoencoder (JT-VAE).

Yuan, Z. and Dong, D.M. (2022) Near-Infrared Spectroscopy Measurement of Contrastive Variational Autoencoder and Its Application in the Detection of Liquid Sample. Spectroscopy and Spectral Analysis, ...

Autoencoder models of source code are an emerging alternative to autoregressive large language models with important benefits for genetic improvement of software. We hypothesize that encoder-decoder ...

Article citations More>> Jin, W., Barzilay, R. and Jaakkola, T. (2018) Junction Tree Variational Autoencoder for Molecular Graph Generation. International Conference on Machine Learning, Stockholm, 10 ...

Soon after announcing the general availability of Windows Server 2025, Microsoft released a Windows Server 2025 Security features PDF covering how Windows Server and related Azure security ...

Introduction: Dementia, characterized by cognitive decline and impaired judgment, imposes a significant economic burden due to its rising prevalence and high diagnostic costs. Recent research has ...