581 datasets found

A dataset of peptide sequences used for training and testing the proposed CLaSS method for controlled generation of antimicrobial peptides.

A general framework for learning perturbation sets from data when the perturbation cannot be mathematically-defined.

The dataset is a two-dimensional turbulent flow, analyzed using a convolutional autoencoder echo state network (CAE-ESN) for spatiotemporal decomposition and prediction of...

The USPS Handwritten binary Alphadigits dataset consists of binary images with size 20 × 16, with digits of “0” through “9” and capital “A” through “Z”, with 39 examples of each...

A study of the behavior of several methods for balancing machine learning training data

A machine-learning data set prepared from the NASA Solar Dynamics Observatory mission.

Realistic real-time talking head synthesis with hash grid landmarks encoding and progressive multilayer conditioning

The dataset used in the paper is the custom function, which is a 2-dimensional function with 6 categorical variables.

The dataset used in the paper is the wing weight model, which is a 2-dimensional function with 3 categorical variables.

The dataset used in the paper is the effective potential model, which is a 2-dimensional function with 5 categorical variables.

The dataset used in the paper is the piston simulator model, which is a 2-dimensional function with 3 categorical variables.

The dataset used in the paper is the OLT circuit model, which is a 2-dimensional function with 3 categorical variables.

The dataset used in the paper is the borehole function, which is a 8-dimensional function with 3 categorical variables.

This dataset contains images of cats and dogs, which is used for training deep neural networks.

A dataset of interatomic potentials for training machine learning models.

A broad benchmark for applying machine learning models to solid-state materials.

The dataset used in the paper is a two-layer neural network with a single-neuron target function.

Networked science in machine learning.

The dataset is used to represent data points through attribute values using measure theoretic basis for fuzzy theoretic analytical deep models.

Calibration tests in multi-class classification: A unifying framework