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Density Estimation On Cifar 10

Metrics

NLL (bits/dim)

Results

Performance results of various models on this benchmark

		Paper Title	Repository
DDPM	3.69	Denoising Diffusion Probabilistic Models
MRCNF	3.54	Multi-Resolution Continuous Normalizing Flows
FFJORD	3.4	FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models
RNODE	3.38	How to train your neural ODE: the world of Jacobian and kinetic regularization
Pixel CNN	3.03	Conditional Image Generation with PixelCNN Decoders
Flow matching	2.99	Flow Matching for Generative Modeling
score SDE	2.99	Score-Based Generative Modeling through Stochastic Differential Equations
Pixel CNN ++	2.92	PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications
Image Transformer	2.90	Image Transformer	-
VDM	2.65	Variational Diffusion Models
BSI	2.64	Generative Modeling with Bayesian Sample Inference
MULAN	2.55	Diffusion Models With Learned Adaptive Noise
i-DODE	2.42	Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs
MAF	-	Masked Autoregressive Flow for Density Estimation

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Density Estimation On Cifar 10 | SOTA | HyperAI