Category: Generative Modeling
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Evaluating Synthetic Data — The Million Dollar Question
Evaluating Synthetic Data — The Million Dollar Question Learn how to evaluate synthetic data quality using the Maximum Similarity Test — a simple, quantitative approach for assessing fidelity, utility, and privacy in synthetic datasets. The post Evaluating Synthetic Data — The Million Dollar Question appeared first on Towards Data Science. Andrew Skabar Go to original…
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Why Nonparametric Models Deserve a Second Look
Why Nonparametric Models Deserve a Second Look Discover how nonparametric conditional distributions unify regression, classification, and synthetic data generation—without assuming functional forms. The post Why Nonparametric Models Deserve a Second Look appeared first on Towards Data Science. Andrew Skabar Go to original source
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From Physics to Probability: Hamiltonian Mechanics for Generative Modeling and MCMC
From Physics to Probability: Hamiltonian Mechanics for Generative Modeling and MCMC Phase space of a nonlinear pendulum. Photo by the author. Hamiltonian mechanics is a way to describe how physical systems, like planets or pendulums, move over time, focusing on energy rather than just forces. By reframing complex dynamics through energy lenses, this 19th-century physics…