However, most existing autoencoder-based methods discard the reconstruction of auxiliary information, which poses a huge challenge for better representation learning and model scalability.

Chen Qiao, Yuanhua Huang, Representation learning of RNA velocity reveals robust cell transitions, Proceedings of the National Academy of Sciences of the United States of America, Vol. 118, No. 49 ...

An autoencoder is an unsupervised learning model designed to encode input data into a lower-dimensional feature representation through the encoder, and then reconstruct the original input data as ...