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 ...

The structural diversity of chemical libraries, which are systematic collections of compounds that have potential to bind to biomolecules, can be represented by chemical latent space. A chemical ...

This study led to the development of a variational autoencoder (VAE) for estimating the chronological age of subjects using feature values extracted from their teeth. Further, it determined how given ...

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 ...

Applications of Autoencoders are vast and they are an interesting and practical type of artificial neural network, especially popular in the field of deep learning. This guide will cover key aspects ...

VAE（Variational AutoEncoder）は、2013年の論文「Auto-Encoding Variational Bayes」（変分ベイズ自動エンコーディング）の中で発表されたデータ生成の手法を使ったモデルの名前です。 オランダにあるアムステルダム大学のDiederik P KingmaとMax Wellingは、彼らの手法をAEVB ...

VQVAEは、オートエンコーダの一種で、特に高解像度の画像を生成するのに適した手法です。 深層学習の種類の中にオートエンコーダがあります オートエンコーダ（自己符号化器, autoencoder）とは、ニューラルネットワークを利用した教師なし機械学習の手法 ...

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 ...

This project presents a comprehensive implementation of a Variational Autoencoder system designed for unsupervised anomaly detection in high-dimensional datasets. The implementation emphasizes ...

Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...