Detect Anomalies in Text Data Using Variational Autoencoder (VAE) in MATLAB® This example shows how to detect out-of-distribution text data using a variational autoencoder (VAE).

This folder implements MAE operations. Key components of transformers are located inside +layers. To run the code: To visualize the attention map, run MAE_inference_vit_[base/large].m. This will ...

We proposed a convolutional autoencoder with sequential and channel attention (CAE-SCA) to address this issue. Sequential attention (SA) is based on long short-term memory (LSTM), which captures ...

This paper proposes an autoencoder (AE) framework with transformer encoder and extended multilinear mixing model (EMLM) embedded decoder for nonlinear hyperspectral anomaly detection. Specifically, ...

The autoencoder network model for HIV classification, proposed in this paper, thus outperforms the conventional feedforward neural network models and is a much better classifier.