Synthetic data
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- Multitask Principal Component Analysis
- The Confounding Problem of Private Data Release
- Confounding-Robust Policy Improvement
- Variational Bayesian Autoregressive Conditional Heteroskedastic Models
- Topics and Applications in Synthetic Data
- Using Permutations to Detect, Quantify and Correct for Confounding in Machine Learning Predictions
- Real-Time Algorithms for the Detection of Changes in the Variance of Video Content Popularity Sotiris Skaperas, Lefteris Mamatas, Arsenia Chorti
- Growing Synthetic Data Through Differentially-Private Vine Copulas
- Relative Forecasting Performance of Volatility Models: Monte Carlo Evidence by Thomas Lux and Leonardo Morales-Arias
- A Neural Stochastic Volatility Model
- Identification of Confounder in Epidemiologic Data Contaminated by Measurement Error in Covariates Paul H
- AI and Synthetic Data
- Performance Analysis of Some Machine Learning Algorithms for Regression Under Varying Spatial Autocorrelation
- Mtcopula: Synthetic Complex Data Generation Using Copula
- Tests for Conditional Heteroscedasticity with Functional Data and Goodness-Of-fit Tests for FGARCH Models
- Synthetic Data for Small Area Estimation in the American Community Survey
- Assessing Validity of Synthetic Data Inferences
- Satisfying Disclosure Restrictions with Synthetic Data Sets