인간-중심-자동화를-위한-이동성-자원-maar-

metabolism-s-role-in-sex-specific-kidney-disease-outcomes

lernen-eines-multi-task-transformators-durch-vereinheitlichtes-und-angepasstes-anweisungstuning-für-die-interpretation-von-brustradiographien

neuro-gpt-ein-grundlagenmodell-für-eeg

effiziente-verarbeitung-und-analyse-von-inhalten-für-erkenntnisse-in-taobao-suche

mobility-as-a-resource-maar-for-resilient-human-centric-automation-a-vision-paper

신뢰할-수-있는-정보를-제공하는-침입-탐지를-위한-양자화-인식-신경-구조-검색

intravascular-lithotripsy-for-mitral-valve-stenosis-a-promising-treatment-approach


Least Volume regularization can compress the latent representation of a dataset into a low dimensional latent subspace without sacrificing reconstruction performance, by leveraging the Lipschitz continuity of the autoencoder's decoder.


coremsg

compressing-latent-space-via-least-volume-regularization-for-autoencoders


Compressing Latent Space via Least Volume Regularization for Autoencoders


title_rewrite

Latent Space Compression in Autoencoders