Research map / Probabilistic and scientific modeling / Uncertainty and Gaussian processes
Robust Neural Posterior Estimation and Statistical Model Criticism
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| replace NPE with RNPE (spike-and-slab error model, denoising) | NPE · SIR beta | MSE: 1.10 -> 0.13 | Helped |
| replace NPE with RNPE | NPE · Gaussian mu | MSE: 0.17 -> 0.02 | Helped |
| replace NPE with RNPE | NPE · CS lambda_d | MSE: 1.92 -> 1.21 | Helped |
| replace NPE with RNPE | NPE · Gaussian Linear | MSE: 0.75 -> 0.70 | No clear effect |
| replace NPE with RNPE | NPE · CS lambda_c | MSE: 0.12 -> 0.13 | No clear effect |
| explicitly denoise with learned q(x) (RNPE) instead of adding the error model inside the simulator (NNPE) | NNPE · misspecified tasks, log prob of true parameters | log probability of true parameters | Helped |
| replace NPE with RNPE | NPE · misspecified tasks, coverage | posterior coverage | Helped |
| use RNPE on a well-specified simulator | NPE · well-specified tasks | log probability of true parameters | Hurt |
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