Research map / Probabilistic and scientific modeling / Variational and generative sampling
Select-and-Sample for Spike-and-Slab Sparse Coding
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add subspace preselection (H'=5 of H=10) before Gibbs sampling in S5C (ablation) | S5C on artificial bars ground-truth data · Artificial bars data (H=10) | runs recovering all generating bars: 9/10 runs vs 2/10 runs without preselection | Helped |
| Scale select-and-sample spike-and-slab sparse coding to H=10,000 latents | S5C · van Hateren image patches 16x16 | latent dimensionality | Helped |
| Use sampling within selected subspaces instead of exhaustive summation (ET-GSC) | S5C · House denoising sigma=25 | PSNR | Helped |
| Increase number of samples per subspace | S5C · House denoising | PSNR | Helped |
| Increase number of latents H beyond 256 | S5C · House denoising | PSNR | No clear effect |
Closest papers by meaning
- Scalable Spike-and-Slab (ICML 2022 · similarity 0.89)
- Training Bayesian Neural Networks with Sparse Subspace Variational Inference (ICLR 2024 · similarity 0.87)
- Complex priors and flexible inference in recurrent circuits with dendritic nonlinearities (ICLR 2024 · similarity 0.86)
- Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithm (NeurIPS 2024 · similarity 0.86)
- Posterior Contraction Rates for sparse Kolmogorov-Arnold Networks in Anisotropic Besov Spaces (NeurIPS 2026 · similarity 0.86)
- Posterior Inference in Latent Space for Scalable Constrained Black-box Optimization (NeurIPS 2026 · similarity 0.85)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.