Akhila Ram

From Predictors to Samplers via the Training Trajectory

Sampling from trained predictors is fundamental for interpretability and as a compute-light alternative to diffusion models, but local samplers struggle on the rugged, high-frequency functions such models learn. We observe that standard neural‑network training implicitly produces a coarse‑to‑fine se…