IEEE

Study on Efficiency Map Prediction of Synchronous Motors Using Tandem Variational Autoencoder-Based Surrogate Model

Abstract: To reduce the computational cost of finite-element analysis for rapid optimal motor design, surrogate modeling techniques have been widely studied. While conventional surrogate models mainly ...
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 ...
IEEE

A Generative Model for Cetacean Whistles Using Variational Autoencoder and Mixture of Gaussians

Abstract: This paper proposes a tractable and compact generative model for cetacean whistle signals based on Variational Autoencoder (VAE) and mixture of Gaussians in underwater biomimetic ...
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 ...
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.