This repository contains the code for the lecture "Big Data Praktikum SS25". The objective was to train a variational autoencoder (VAE) on cellxgene data and find meaningful latent representations of ...

ABSTRACT: Extreme learning machine (ELM) is a feedforward neural network-based machine learning method that has the benefits of short training times, strong generalization capabilities, and will not ...

The primary objective of this project is to develop an efficient model for data compression. The focus is on leveraging complex autoencoder architectures to achieve significant dimensionality ...

This process is called Autoencoder, which can be used to not only for image recognifition, but it can also be used to non-linear simulation like GAN (Generative Adversarial Network). To further ...

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 ...

Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...

ABSTRACT: Video-based anomaly detection in urban surveillance faces a fundamental challenge: scale-projective ambiguity. This occurs when objects of different physical sizes appear identical in camera ...