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 ...

The primary goal of this project was to explore the use of deep learning, specifically an autoencoder, for generating pseudo-random data that exhibits similar characteristics to a given training ...

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 ...

Abstract: The practical realization of end-to-end training of communication systems is fundamentally limited by its accessibility of the channel gradient. To overcome this major burden, the idea of ...

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 ...

This project uses a Keras/TensorFlow Autoencoder to identify anomalous traffic patterns in an AWS Elastic Load Balancer (ELB) request count dataset. The goal is to build an unsupervised learning model ...

Abstract: In this paper, we propose a novel Transformer based approach, namely Cross-modal Contrastive Masked AutoEncoder (C2MAE), to Self-Supervised Learning (SSL) on compressed videos. A unified ...