Recovery Guarantees for Posterior Sampling of One-Bit Compressed Sensing
The authors investigate reliable recovery from noisy one-bit compressed sensing when signals follow arbitrary prior distributions. They prove that posterior sampling achieves accurate recovery if measurement counts scale with the logarithm of the approximate covering number, establishing this as a necessary information-theoretic lower bound for this problem.