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2 results for FFJORD

FFJORD models generate complex distributions efficiently with unbiased density estimation.

problem Efficiently generating complex distributions with unbiased density estimation.
method FFJORD uses continuous-time invertible neural networks with Hutchinson's trace estimator for unbiased log-density estimation.
result FFJORD achieves state-of-the-art performance in high-dimensional density estimation, image generation, and variational inference.

Gaussianization flows transform any random vector into a Gaussian, enabling efficient computation and sample generation.

problem Transforming any random vector into a Gaussian for efficient computation and sample generation.
method Iterative Gaussianization and normalizing flow model.
result Gaussianization flows are universal approximators and achieve better performance on tabular datasets.