Research map / Probabilistic and scientific modeling / Variational and generative sampling
Challenges and Opportunities in High Dimensional Variational Inference
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| apply PSIS correction to exclusive KL approximation (ablation) | BBVI exclusive KL · posteriordb radon | predictive log-likelihood: -353.0 -> -325.0 | Helped |
| apply PSIS correction to exclusive KL approximation (ablation) | BBVI exclusive KL · posteriordb diamonds | predictive log-likelihood: -2.6 -> 1.5 | Helped |
| apply PSIS correction to exclusive KL approximation (ablation) | BBVI exclusive KL · posteriordb mesquite | predictive log-likelihood: -2512 -> -5418 | Hurt |
| apply PSIS correction to exclusive KL approximation (ablation) | BBVI exclusive KL · posteriordb nes1996 | predictive log-likelihood: -412.8 -> -427.9 | Hurt |
| apply PSIS correction to inclusive KL approximation (ablation) | BBVI inclusive KL · posteriordb dogs | predictive log-likelihood: -110 -> -70.5 | Helped |
| apply PSIS correction to inclusive KL approximation (ablation) | BBVI inclusive KL · posteriordb nes1996 | predictive log-likelihood: -2140.5 -> -499.3 | Helped |
| use exclusive KL instead of inclusive KL | BBVI · posteriordb diamonds | predictive log-likelihood: -3196.6 -> -2.6 | Helped |
| use exclusive KL instead of inclusive KL | BBVI · posteriordb radon | predictive log-likelihood: -377.4 -> -353.0 | Helped |
| use exclusive KL instead of inclusive KL | BBVI · posteriordb dogs | predictive log-likelihood: -110 -> -71.2 | Helped |
| use exclusive KL instead of inclusive KL in low dimension | BBVI · posteriordb arK (D=7) | predictive log-likelihood: -34.3 -> -35.2 | Hurt |
| increase target dimension D from 2 to 50 with inclusive KL | mean-field and flow BBVI · robust regression | Pareto k-hat | Hurt |
| use normalizing-flow family with inclusive KL | BBVI · robust regression | largest converged dimension: D = 2 | Hurt |
Closest papers by meaning
- Provably Scalable Black-Box Variational Inference with Structured Variational Families (ICML 2024 · similarity 0.92)
- Nearly Dimension-Independent Convergence of Mean-Field Black-Box Variational Inference (NeurIPS 2025 · similarity 0.92)
- EigenVI: score-based variational inference with orthogonal function expansions (NeurIPS 2024 · similarity 0.91)
- Efficient Mixture Learning in Black-Box Variational Inference (ICML 2024 · similarity 0.91)
- Batch and match: black-box variational inference with a score-based divergence (ICML 2024 · similarity 0.90)
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