note

機械学習モデルの実装：AutoEncoder（Pytorch）

本記事ではAutoEncoderをPytorchで実装します。ライブラリ紹介ではなく実装がメインのため学習シリーズに近い内容となります。 AutoEncoderの特徴は下記の通りです。 情報を圧縮することで軽い動作で使用できる。 ー＞本記事では784次元の画像を200次元（潜在 ...
GitHub

Digits_Master /examples /autoencoder

An image autoencoder may be used to learn a compressed representation of an image. An autoencoder comprises two parts: an encoder, which learns a representation of the image, using fewer neurons than ...
Visual Studio Magazine

Autoencoder Anomaly Detection Using PyTorch

The Data Science Lab Autoencoder Anomaly Detection Using PyTorch Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a ...
GitHub

LSTM-autoencoder with attentions for multivariate time series

","","This repository contains an autoencoder for multivariate time series forecasting.","It features two attention mechanisms described in *[A Dual-Stage Attention ...
Frontiers

Generation and discrimination of autism MRI images based on autoencoder

This study aims to explore an autoencoder-based method for generating brain MRI images of patients with Autism Spectrum Disorder (ASD) and non-ASD individuals, and to discriminate ASD based on the ...
日経クロステック

Masked Autoencoder：画像認識でも事前学習革命は起きるのか

この記事は日経Robotics 有料購読者向けの過去記事ですが 『日経Robotics デジタル版（電子版）』のサービス開始を記念して、特別に誰でも閲覧できるようにしています。 本記事はロボットとAI技術の専門誌『日経Robotics』のデジタル版です [画像のクリックで ...
IEEE

An Outlier-Resilient Autoencoder for Representing High-Dimensional and Incomplete Data

Abstract: High-dimensional and incomplete (HDI) data commonly arise in various Big Data-related applications, e.g., recommender systems and bioinformatics. Representation is a learning paradigm to map ...
IEEE

Detecting Adversarial Examples in Learning-Enabled Cyber-Physical Systems using Variational ...

Abstract: Learning-enabled components (LECs) are widely used in cyber-physical systems (CPS) since they can handle the uncertainty and variability of the environment and increase the level of autonomy ...