Research map / Probabilistic and scientific modeling / Variational and generative sampling
Hierarchical Implicit Models and Likelihood-Free Variational Inference
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Bayesian GAN rather than Bayesian neural network with VI | Bayesian classification · Crabs | test set error: 0.02 -> 0.03 | Hurt |
| Use Bayesian GAN rather than Bayesian neural network with VI | Bayesian classification · Pima | test set error: 0.242 -> 0.232 | Helped |
| Use Bayesian GAN rather than Bayesian neural network with VI | Bayesian classification · Covertype | test set error: 0.164 -> 0.154 | Helped |
| Use Bayesian GAN rather than Bayesian neural network with VI | Bayesian classification · MNIST | test set error: 0.0311 -> 0.0136 | Helped |
| Use VI rather than MAP (ablation) | Bayesian GAN classification · Crabs | test set error: 0.12 -> 0.03 | Helped |
| Use VI rather than MAP (ablation) | Bayesian GAN classification · Pima | test set error: 0.240 -> 0.232 | Helped |
| Use VI rather than MAP (ablation) | Bayesian GAN classification · Covertype | test set error: 0.185 -> 0.154 | Helped |
| Use VI rather than MAP (ablation) | Bayesian GAN classification · MNIST | test set error: 0.0283 -> 0.0136 | Helped |
| Use hinge loss rather than log loss for ratio estimation (ablation) | LFVI on Lotka-Volterra · Lotka-Volterra simulator | posterior accuracy | No clear effect |
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