Abstract: Health indicator (HI) affects the accuracy and reliability of the remaining useful life (RUL) prediction model. The hidden variables of variational autoencoder (VAE) can represent the HI ...
Abstract: Variational Autoencoder(VAE) combines the ideas of autoencoders and variational inference, introducing the concept of latent space and variational inference to endow autoencoders to generate ...
Recent advances in feature selection methods for breast cancer recurrence prediction: A systematic review. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...
ABSTRACT: Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs when objects of different physical sizes appear identical in camera ...
This project presents a comprehensive implementation of a Variational Autoencoder system designed for unsupervised anomaly detection in high-dimensional datasets. The implementation emphasizes ...
An autoencoder is a neural network architecture that learns to compress data into a lower-dimensional representation and then reconstruct it. The network consists of an encoder that maps input to a ...
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