Research map / Probabilistic and scientific modeling / Causal discovery
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Evaluate latent features with IRS alongside FI and MI | DIP-VAE representations on dSprites · dSprites | robustness detection: top 18% -> bottom 4% | Helped |
| Use interventions on nuisance factors to assess feature stability | DIP-VAE feature Z6 on dSprites · dSprites | feature robustness | Hurt |
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