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"schema_version": 1,
"title": "Reproduction: Predictive Variational Inference (PVI)",
"emoji": "🎯",
"space_id": "snaykey/repro-predictive-vi",
"paper": {
"openreview_id": "dVIts0fNb4"
},
"tags": [
"icml2026-repro",
"paper-dVIts0fNb4"
],
"updated_at": "2026-08-02T00:00:00+00:00",
"root": {
"slug": "index",
"title": "Reproduction: Predictive Variational Inference (PVI)",
"file": "pages/index.md",
"children": [
{
"slug": "claim-1-framework",
"title": "Predictive variational inference (PVI) replaces the KL-divergence objective of standard VI with optimization of the posterior predictive distribution against the true data-generating process, using proper scoring rules (Section: Main Framework).",
"file": "pages/claim-1-framework/page.md",
"children": []
},
{
"slug": "claim-2-prop1-consistency",
"title": "Proposition 1 establishes that PVI solutions converge to the predictively optimal parameter as sample size grows, even under model misspecification (Proposition 1).",
"file": "pages/claim-2-prop1-consistency/page.md",
"children": []
},
{
"slug": "claim-3-corollaries",
"title": "Corollary 1 shows PVI recovers the true parameter when the model is correctly specified, and Corollary 2 shows it recovers the population parameter distribution when misspecified with population-varying parameters (Corollary 1, Corollary 2).",
"file": "pages/claim-3-corollaries/page.md",
"children": []
},
{
"slug": "claim-4-scoring-rules",
"title": "PVI is implemented with three proper scoring rules -- logarithmic, quadratic, and continuous ranked probability score (CRPS) -- with the CRPS variant enabling likelihood-free inference for intractable simulators (Section on scoring rules).",
"file": "pages/claim-4-scoring-rules/page.md",
"children": []
},
{
"slug": "claim-5-cryoem-heterogeneity",
"title": "In a cryo-EM protein conformation inference experiment, PVI recovers the true population distribution of parameters while standard Bayesian VI collapses to a point estimate (Section: CryoEM Protein Inference experiment).",
"file": "pages/claim-5-cryoem-heterogeneity/page.md",
"children": []
},
{
"slug": "claim-6-posteriordb",
"title": "Across 7 models from PosteriorDB, PVI improves held-out predictive performance compared to standard variational inference (Section: Benchmark PosteriorDB experiment).",
"file": "pages/claim-6-posteriordb/page.md",
"children": []
},
{
"slug": "executive-summary",
"title": "executive-summary",
"file": "pages/executive-summary/page.md",
"children": []
},
{
"slug": "conclusion",
"title": "conclusion",
"file": "pages/conclusion/page.md",
"children": []
}
]
}
}
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