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Score-based generative models (SGMs) are a recent breakthrough in generating fake images.
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Adversarial score matching and improved sampling for image generation
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BAGAN: Data Augmentation with Balancing GAN
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Global-and-local aware data generation for the class imbalance problem. In ICDM . SIAM, 307–315
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Conditional Wasserstein GAN-based Oversampling of Tabular Data for Imbalanced Learning
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Invertible Tabular GANs: Killing Two Birds with One Stone for Tabular Data Synthesis. In NeurIPS
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Score-Based Generative Modeling through Stochastic Differential Equations. In ICLR
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Score-Based Generative Modeling with Critically-Damped Langevin Diffusion. In ICLR
Tim Dockhorn, Arash Vahdat, and Karsten Kreis. 2022 · 2022
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Tackling the Generative Learning Trilemma with Denoising Diffusion GANs. In ICLR
Zhisheng Xiao, Karsten Kreis, and Arash Vahdat. 2022 · 2022
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