IEEE

A Neural-Network-Based Statistical Compact Model Using a Variational Autoencoder for Emerging Transistors

Abstract: Emerging transistors lack the statistical compact models needed to evaluate the yield of integrated circuits. To address this, we propose a novel framework combining a variational ...
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

Fault Detection and Identification of Underwater Thruster Without Fault Sample Based on Adversarial Variational Autoencoder

Abstract: This article proposes a new underwater thruster fault detection and identification method based on adversarial variational autoencoder (AdvVAE). Adversarial training and variational ...
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.