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Adaptive Multi-stage Density Ratio Estimation for Learning Latent Space Energy-based Model

NeurIPS 2022 · Probabilistic and scientific modeling › Variational and generative sampling · approach: Importance sampling and quadrature · 2 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
replace a simple latent Gaussian prior with the learned adaptive multi-stage latent EBMgenerator model · SVHN, CelebA, CIFAR-10FID: 29.44 -> 26.19; 37.87 -> 35.38; 70.15 -> 65.01Helped
replace LEBM with adaptive multi-stage latent EBM traininggenerator model · SVHN, CelebA, CIFAR-10MSE: 0.008 -> 0.004; 0.013 -> 0.009; 0.020 -> 0.008Helped
replace LEBM with adaptive multi-stage latent EBM traininggenerator model · MNIST heldout digits 1, 4, 5, 7, 9AUPRC: 0.336± 0.01 -> 0.531 ± 0.02; 0.630± 0.02 -> 0.729 ± 0.02; 0.619± 0.01 -> 0.742 ± 0.01; 0.463 ± 0.01 -> 0.620 ± 0.02; 0.4Helped
add a learned latent EBM instead of using only the base Gaussian prior (ablation)Adaptive CE · CelebAFID: 62.78 -> 44.17Helped
add multiple density-ratio stages rather than use single-stage estimation (ablation)Adaptive CE · CelebAFID: 44.17 -> 35.38Helped
increase adaptive training from 4 to 8 density-ratio stages (ablation)Adaptive CE · CelebAFID: 35.38 -> 35.84Hurt
replace adaptive sequential training with non-adaptive training at 1 stage (ablation)multi-stage density-ratio estimation · CelebAFID: 44.17 -> 43.84Hurt
replace adaptive sequential training with non-adaptive training at 2 stages (ablation)multi-stage density-ratio estimation · CelebAFID: 39.85 -> 42.61Hurt
replace adaptive sequential training with non-adaptive training at 4 stages (ablation)multi-stage density-ratio estimation · CelebAFID: 35.38 -> 42.48Hurt
replace adaptive sequential training with non-adaptive training at 8 stages (ablation)multi-stage density-ratio estimation · CelebAFID: 35.84 -> 43.06Hurt
increase model size of a single-stage latent EBM to 4× (ablation)single-stage latent EBM · CelebAFIDNo clear effect

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