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 ...
Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management.
On September 11, Gelonghui reported that Jingzhida (688627.SH) stated on its interactive platform that the company continues to innovate technology and develop intellectual property in the ...
PyTorch reimplementation of "Deep Hierarchical Planning" RL framework. Features a multi-model architecture with manager-worker policies, world model, and goal autoencoder. Built with Python/PyTorch ...
Abstract: Masked Autoencoder (MAE) has shown remarkable potential in self-supervised representation learning for 3D point clouds. However, these methods primarily rely on point-level or low-level ...
The ambition of brain-inspired Spiking Neural Networks (SNNs) is to become a low-power alternative to traditional Artificial Neural Networks (ANNs). This work addresses two major challenges in ...
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