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05/19/2023
Generative Sliced MMD Flows with Riesz Kernels
Maximum mean discrepancy (MMD) flows suffer from high computational cost...
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03/28/2023
Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems
Conditional generative models became a very powerful tool to sample from...
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01/27/2023
Neural Wasserstein Gradient Flows for Maximum Mean Discrepancies with Riesz Kernels
Wasserstein gradient flows of maximum mean discrepancy (MMD) functionals...
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05/24/2022
PatchNR: Learning from Small Data by Patch Normalizing Flow Regularization
Learning neural networks using only a small amount of data is an importa...
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01/20/2022