InfoWorld

AI-augmented data quality engineering

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...
GitHub

Attention-Guided Vector Quantized Variational Autoencoder for Brain Tumor Segmentation

Additional visualizations highlighting the comparison between the proposed two-stage AG-VQ-VAE network (without skip connections) and the single-stage AG-UNet (with skip connections) are presented.
IEEE

Semantic Underwater Optical Wireless Communication Using Variational Autoencoders

Abstract: The emergence of internet of underwater things has increased the demand for high-quality underwater image transmission across various applications, including infrastructure inspection and ...
GitHub

Graph Positional Autoencoders as Self-supervised Learners (GraphPAE)

accelerate==0.33.0 numpy==1.24.4 ogb==1.3.6 pandas==2.2.3 PyYAML==6.0.2 rdkit_pypi==2022.9.5 scikit_learn==1.3.2 scipy==1.8.1 torch==2.1.2+cu121 torch_geometric==2.6.1 torch_scatter==2.1.2+pt21cu121 ...
IEEE

Unsupervised Texture Analysis of Downhole Videos Using Variational Autoencoders

Abstract: Optimizing drill and blast processes in surface mining enhances material fragmentation, leading to millions of dollars of cost and significant energy savings every year. Understanding the ...
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 ...