9 datasets found

The dataset used in the paper is the COIL dataset for testing the proposed autoencoder-based method for post-nonlinear mixture learning.

The dataset used in the paper is the Moffett field dataset for testing the proposed autoencoder-based method for post-nonlinear mixture learning.

The dataset used in the paper is a synthetic dataset for testing the proposed autoencoder-based method for post-nonlinear mixture learning.

The dataset is not explicitly described in the paper, but it is mentioned that the authors used a simple autoencoder to learn a low-order representation of the turbulent flow.

The dataset used in the paper is a collection of one-hot vectors representing the position of a Dirac delta function.

The dataset used in the paper is a collection of grey-level images of centred disks with varying radii.

The dataset used in the paper is the CLIC professional-train dataset, which contains images that are too large to fit into the eight gigabytes memory of Nvidia Geforce GTX1070.

The dataset used in this paper is a collection of indoor environment data time-series, including temperature, relative humidity, and CO2 concentration.

A dataset used for training and testing the autoencoder (AE) and Classification Without Labels (CWoLa) techniques for resonant anomaly detection.