AI RESEARCH
Optimal Stability of KL Divergence under Gaussian Perturbations
arXiv CS.AI
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ArXi:2604.11026v1 Announce Type: cross We study the problem of characterizing the stability of Kullback-Leibler (KL) divergence under Gaussian perturbations beyond Gaussian families. Existing relaxed triangle inequalities for KL divergence critically rely on the assumption that all involved distributions are Gaussian, which limits their applicability in modern applications such as out-of-distribution (OOD) detection with flow-based generative models.