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Machine Learning and Factor-Based Portfolio Optimization
The dataset consists of monthly total individual stock returns from the Center for Research in Security Prices (CRSP) starting on January 1960 to December 2019, for a period of... -
Change Detection in Graph Streams by Learning Graph Embeddings on Constant-Cu...
The dataset is a stream of attributed graphs, where each graph is a 3-tuple of matrices (A, X, E) representing the topology and attributes of the graph. -
Boosting the performance of anomalous diffusion classifiers with the proper c...
Understanding and identifying different types of single molecules' diffusion that occur in a broad range of systems (including living matter) is extremely important, as it can... -
Identification of Anomalous Diffusion Sources by Unsupervised Learning
Fractional Brownian motion (fBm) is a ubiquitous diffusion process in which the memory effects of the stochastic transport result in the mean squared particle displacement... -
Functional Priors and Posteriors from Data and Physics
The dataset used in this paper is a collection of historical data for learning functional priors and posteriors from data and physics. -
Noisy wheel dataset
The dataset used in the paper is a noisy wheel dataset, which is a 2-D Euclidean space with inner circles that regulate the class proportions. -
UCI datasets
The dataset used in the paper is a set of UCI datasets, including adult, census, covertype, financial, joke, mushroom, and statlog. -
WIT: Wikipedia-based image text dataset for multimodal multilingual machine l...
A multimodal dataset for machine learning tasks, focusing on Wikipedia-based image text datasets. -
Simulated AT-TPC dataset
The dataset used in this paper is a collection of simulated 2D projections of particle tracks from a resonant proton scattering experiment on 46Ar. -
AT-TPC dataset
The dataset used in this paper is a collection of 2D projections of particle tracks from a resonant proton scattering experiment on 46Ar. -
UEFA EURO 2020 and 2022 location data
The dataset used in this study is the open-source location data of all players in broadcast video frames in football games of men’s Euro 2020 and women’s Euro 2022 competitions. -
ε-greedy Thompson Sampling
Two benchmark functions (2d Ackley and 6d Rosenbrock) and a steel cantilever beam dataset -
High-Dimensional Linear Composites
The dataset used in this paper is a collection of high-dimensional linear composites with outer function f and general data-covariance. -
FK-RFE: A Model-Free Feature Selection Procedure for Ultra-High Dimensional Data
A model-free feature selection procedure for ultra-high dimensional data with mass features. -
Physical exercise, Iris, Wine, Boston house price, Breast cancer, Epilepsy
The Physical exercise data set contains data about physical exercise, Iris data set contains data about iris plants, Wine data set contains data about wine, Boston house price... -
BraTS Challenge
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BraTS challenge. -
A Machine Learning Approach for Player and Position Adjusted Expected Goals i...
Football Event data, including 15,575 shots, used to develop and apply machine learning models for Expected Goals (xG) prediction -
Football Shot Accuracy Dataset
The dataset used in this study for football shot accuracy analysis, containing data from 1000 shots taken by 5 different players. -
Designing Machine Learning Tools to Characterize Multistationarity of Fully O...
A large dataset of labelled fully open CRNs whose production necessitated the development of new CRN theory. -
Fourier Series and Deep Neural Network for the Indicator Function of d-Dimens...
The dataset is used to test the convergence of a deep neural network and a Fourier series for the indicator function of a d-dimensional ball.
