Sampling ideas

Diffusion step schedules, solvers, guidance and stopping rules that cut function evaluations or improve sample quality.

Unverified 2026

Dominance-aware mode extraction for binary neural samplers

Replace nearest-center or k-modes assignment on a pool of binary neural-network samples with responsibility thresholding followed by a coordinate-wise dominance screen. Only retain a candidate mode when its assigned samples are sufficiently explained by that mode and, at every bit position, the responsibility-weighted majority agrees with the proposed center; otherwise mark the mode unreliable or discard it.

Useful5/10
Difficulty4/10
Novelty7/10
Paper: Reliable Sample-Level Quantum Error Mitigation via Dominance-Aware Clustering arXiv:2609.01744
Unverified 2026

Certified partition-function reranking

Replace MAP scoring of discrete latent configurations by comparison of the total energy-model mass assigned to each candidate class. Estimate each class partition function with annealed importance sampling driven by identical random seeds, then return a prediction only when a paired bootstrap confidence interval certifies that its log-partition score exceeds every competitor.

Useful5/10
Difficulty6/10
Novelty6/10
Paper: Certified decoding of quantum LDPC codes arXiv:2608.25545