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

Overall, the application of the Variational Autoencoder not only enhances the analytical capabilities of quantum simulations but also offers new perspectives for understanding the physical properties ...

Essentially all cells in an organism's body have the same genetic blueprint, or genome, but the set of genes that are actively expressed at any given time in a cell determines what type of cell it ...

There is a growing demand for deploying large generative AI models on mobile devices. For recent popular video generative models, however, the Variational AutoEncoder (VAE) represents one of the major ...

├── data_pre/ # Data preprocessing modules │ ├── data_pre.py # Data preprocessing script │ └── dataset.py # Dataset class definition ├── dataset/ # Data directory │ ├── SRU_data.npy # Process data in ...

Researchers at the New Jersey Institute of Technology (NJIT) are using artificial intelligence to address a major challenge in the future of energy storage: finding low-cost, environmentally friendly ...

Researchers from New Jersey Institute of Technology (NJIT) have used artificial intelligence to tackle a critical problem facing the future of energy storage: finding affordable, sustainable ...

Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. Chemical and genetic perturbations, such as ...

Introduction: Wireless Sensor Networks (WSNs) play a critical role in the development of sustainable and intelligent smart city infrastructures, enabling data-driven services such as smart mobility, ...

Abstract: The variational autoencoder (VAE) has proven highly effective in monitoring nonlinear stochastic processes, primarily under the assumption of complete and temporally independent data.