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Generative Learning

Self-Consuming Generative Models with Curated Data Provably Optimize Human Preferences
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Generative Learning 🏢 University of Toronto
Curated synthetic data provably optimizes human preferences in iterative generative model training, maximizing expected reward while mitigating variance.
Generative Forests
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Machine Learning Generative Learning 🏢 Google Research
Generative Forests (GFs) revolutionize tabular data generation with a novel forest-based model and a simple boosting algorithm offering strong convergence guarantees, significantly outperforming curre…
FIDE: Frequency-Inflated Conditional Diffusion Model for Extreme-Aware Time Series Generation
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Machine Learning Generative Learning 🏢 University of Michigan
FIDE, a novel conditional diffusion model, accurately generates time series by inflating high-frequency components, preserving extreme value distributions.
A Generative Model of Symmetry Transformations
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Machine Learning Generative Learning 🏢 University of Cambridge
Generative model learns data symmetries for improved efficiency and higher test log-likelihoods.