normalizing flow vs gan

Keyword	CPC	PCC	Volume	Score	Length of keyword
normalizing flow vs gan	0.92	0.6	6784	51	23
normalizing	1.93	0.3	3989	30	11
flow	0.07	0.8	7143	24	4
vs	1.51	1	7779	59	2
gan	0.41	0.7	1811	25	3

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Keyword	CPC	PCC	Volume	Score
normalizing flow vs diffusion model	0.18	0.4	9149	48
normalizing flow vs variational autoencoder	1.29	0.8	7270	100
spectral normalization for gan	0.08	1	8729	15
gan process flow and machine list	1.81	0.3	8533	86
improved consistency regularization for gans	0.52	0.4	7233	85
continuous normalizing flows github	0.29	0.8	4087	46
normalizing flows across dimensions	1.48	0.2	7224	82
variational graph normalized autoencoders	1.76	0.6	8835	21
autoencoder vs variational autoencoder	1.05	0.7	9687	24
variational quantized variational autoencoder	0.15	0.9	6947	100
variational graph normalized auto-encoders	1.19	0.6	4041	81
variational inference normalizing flows	1.2	0.3	4612	93
variational autoencoder image compression	1.01	0.8	1019	54
variational autoencoder using mixture model	1.07	0.9	7883	62
how to make a variational autoencoder	1.5	0.2	9982	36
introduction to variational autoencoders	0.67	0.4	2611	72
variational autoencoder image generation	0.47	1	7916	61
what is a variational autoencoder	1.45	0.4	8478	95
variational autoencoder for classification	1.51	0.7	6291	31
compressed sensing variational autoencoder	0.84	0.3	658	17
variational autoencoder loss function	0.08	0.4	5118	57
tutorial on variational autoencoders	0.82	0.1	3003	38
applications of variational autoencoders	0.81	0.9	8483	13
variational auto-encoder	0.33	0.7	6706	89
diffusion normalizing flow github	0.89	0.2	491	98
normalization vs flow through	1.73	1	5098	27
normalizing flow-based model	1.15	0.6	507	93
diffusion model regularization loss	1	0.6	8133	23
on the generalization of diffusion model	1.12	0.5	6029	16
diffusion model optical flow	1.6	0.7	4616	43
how to understand diffusion model	0.67	0.9	4732	36
introduction to normalizing flows	1.44	0.5	5736	54
normalizing flow generative model	1.5	0.8	8947	78
introduction to diffusion model	0.28	0.9	4939	28
how to make a diffusion model	0.68	0.4	1393	57
what is a diffusion model	0.76	0.4	4200	80
diffusion model loss not decreasing	0.82	0.6	3328	30
diffusion model in recommendation	1.29	0.8	3798	34
how does a diffusion model work	1.62	0.5	187	48

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