Tag: Deep Generative Models
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Synthetic Trajectory Generators: Utility & Privacy Risks
Explore the balance between utility and privacy in synthetic trajectory generators with our evaluation framework and privacy risk analysis.
Synthetic Trajectory Generators: Utility and Privacy Risks
Explore the balance between utility and privacy in synthetic trajectory generators with new evaluation frameworks and privacy attack insights.
Generating Synthetic Cryptocurrency Data with CGAN Models
Explore how CGANs generate realistic synthetic cryptocurrency price data, enhancing market analysis while ensuring data privacy and efficiency.
Efficient Test-Time Search with Ordered Tokens in AR Models
Discover how coarse-to-fine ordered tokens improve test-time search efficiency and scalability in autoregressive generative models for image synthesis.
Instance-Adaptive VAE for Efficient Variational Inference
Discover how instance-adaptive parametrization improves variational autoencoders, reducing the amortization gap for better inference accuracy and efficienc...