Tech Xplore

Diffusion-based AI model successfully trained in electroplating

Electrochemical deposition, or electroplating, is a common industrial technique that coats materials to improve corrosion ...
Scientific Research Publishing

Prototype-Based Dynamic Autoencoders for Real-Time Anomaly Detection and Explainability ()

Real-time detection of anomalies in data streams is a foundation of modern applied analysis in complex systems. It enables experts to design rapid, efficient, reliable, and high-performance decision ...
GitHub

SVG-T2I: Scaling up Text-to-Image Latent Diffusion Model

Important Note: This repository implements SVG-T2I, a text-to-image diffusion framework that performs visual generation directly in Visual Foundation Model (VFM) representation space, rather than ...
Scientific Research Publishing

A Hybrid CNN-LSTM Variational Autoencoder for Treatment Response Prediction in Synthetic Psychiatric Data ()

Treatment response prediction remains one of the most pressing challenges in precision psychiatry, where patient heterogeneity and complex biomarker interactions limit the reliability of conventional ...
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

The acquisition sites include: CALTECH, California Institute of Technology; CMU, Carnegie Mellon University; KKI, Kennedy Krieger Institute; LEUVEN, University of Leuven; MAX, Ludwig Maximilians ...
C&EN

Mathematical Modeling of Aβ-42 Dimerization Dynamics: Integrating Physics-Based Simulations, Graph-Based Variational Autoencoder-Driven Neural Relational Inference, and Chaos ...

Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahçeşehir University, Istanbul 34349, Turkey Lab for Innovative Drugs (Lab4IND), ...
IEEE

Prior Distribution Guided Gaussian Mixture Variational Autoencoder (PDGM-VAE) for Image Generation

Abstract: Variational Autoencoder(VAE) combines the ideas of autoencoders and variational inference, introducing the concept of latent space and variational inference to endow autoencoders to generate ...
GitHub

VNFlow: Integration of Variational Autoencoders and Normalizing Flows for Novel Molecular Design

This repository accompanies the first report on integrating variational autoencoders with normalizing flows into a comprehensive molecular design workflow. Our approach has generated novel molecules ...