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DeePMD dataset
The dataset is used to train and test the DeePMD model for molecular dynamics simulations. -
Maximizing and Satisficing in Multi-armed Bandits with Graph Information
The dataset used in the paper is a graph-based multi-armed bandit problem with similarity graph information. -
Parametric Differential Machine Learning (PDML) for Pricing and Calibration
The dataset used in this paper is a collection of samples of stochastic processes and functionals, used for training and testing the Parametric Differential Machine Learning... -
Sherpa: Robust Hyperparameter Optimization for Machine Learning
Sherpa is a hyperparameter optimization library for machine learning models. It is specifically designed for problems with computationally expensive, iterative function... -
EEG analytics for early detection of autism spectrum disorder
The dataset used in this study is a collection of EEG signals from individuals with Autism Spectrum Disorder (ASD) and typically developing individuals. -
Diagnosis of Autism through EEG processed by advanced computational algorithms
The dataset used in this study is a collection of EEG signals from individuals with Autism Spectrum Disorder (ASD) and typically developing individuals. -
EEG for Delineating Objective Measure of Autism Spectrum Disorder (ASD)
Autism Spectrum Disorder (ASD) is a developmental disorder that often impairs a child’s normal development of the brain. EEG measures the electric signals of the brain via... -
WEKA library dataset
The dataset of papers per author shows similarity to the distribution of posts per user in social networks. -
Census Income and German Credit datasets
The Census Income (C) and German Credit (G) datasets are used to evaluate the proposed MLClean framework. -
Android Malware Category and Family Detection and Identification using Machin...
Android malware is one of the most dangerous threats on the internet, and its prevalence has increased dramatically in recent years. Experts in cybersecurity face an open... -
GraphEraser: A Novel Machine Unlearning Framework for Graph Data
GraphEraser is a novel machine unlearning framework tailored to graph data. It proposes two novel graph partition algorithms and a learning-based aggregation method to improve... -
Sparse Linear Isotonic Models
The dataset used in this paper is a high-dimensional dataset with a sparse linear isotonic model (SLIM). -
Differentiable Functional Program Interpreters
The dataset used in the paper is a set of input-output examples for program synthesis. The dataset consists of 5 examples for each of 7 tasks, resulting in a total of 35 examples. -
Not specified
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used a combination of datasets from the scikit-learn library and the UCI machine... -
Uncertainty-Aware Learning for Improvements in Image Quality of the Canada-Fr...
The dataset used in this paper is a collection of time series data from various environmental sensors, observatory operating conditions, and image quality measurements. -
Training Set
A dataset used to train and test the neural network classifiers. -
Validation Set
A dataset used to train and test the neural network classifiers. -
Federated Learning for Internet of Things
The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of intelligent services and applications empowered by artificial intelligence... -
Expressive Gaussian mixture models for high-dimensional statistical modelling
Expressive Gaussian mixture models for high-dimensional statistical modelling: simulated data and neural network model files -
Machine Learning and Deep Learning Methods for Intrusion Detection Systems
A survey on machine learning and deep learning methods for intrusion detection systems
