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 ...

Abstract: Effective fault diagnosis for industrial robots is imperative to improve their reliability and availability in safety-critical applications. Proprioceptive signals from servo drive systems ...

※現在、記事作成中のため、ファクトチェックができていない部分がありますので、ご了承ください。 本記事では、初学者の方が理解に苦しみがちな「変分オートエンコーダ（Variational Autoencoder、以下VAE）」について、理論的背景からTensorFlowによる ...

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 ...

In this project, I aim to create a set of images of Kuzushiji Japanese characters via the Kuzushiji-49 dataset using 2 graphical models which are Conditional-Variational Autoencoder(C-VAE), and ...

Abstract: This study introduces a novel approach that combines a variational autoencoder and Bayesian optimization to accelerate the simultaneous parameter and topology optimization of interior ...

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

Multiomics data integration with machine learning has become the standard approach for combining genomic, transcriptomic, proteomic, and metabolomic measurements collected from the same biological ...