Empirical Study Finds Uncertainty Quantification in Genomics Deep Learning Is Largely Unvalidated

arXiv 2608.11054·low signalXBlueskyLinkedInCopy link

Deep learning is now the standard computational tool across genomics applications, but the reliability of the uncertainty estimates those models produce has received little systematic attention. This empirical analysis evaluates uncertainty quantification methods specifically in genomics settings, testing whether commonly used estimates actually behave as claimed. The broader lesson for practitioners is that UQ methods imported wholesale from vision and NLP into a new domain should not be assumed calibrated there — a caution that applies well beyond genomics.