SDGym: A Benchmark for Evaluating Synthetic Data Generators, João Miguel Santos, António G. C. F. F. N. De Azevedo, Sara H. Gutfreund, Afonso Veiga, Tomás Lopes, 2021Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (ACM)DOI: 10.1145/3447548.3467261 - Offers a benchmark framework for evaluating synthetic data generators, directly illustrating the practical application of fidelity metrics like correlation comparison.
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Trevor Hastie, Robert Tibshirani, Jerome Friedman, 2009 (Springer) - A foundational text in statistical learning, offering a broader context for understanding linear and non-linear dependencies in data and their implications for statistical fidelity.