differentiable

This paper introduces REVEAL++, a differentiable phenotypic grouping method for vision-language contrastive learning, applied to retinal fundus images and clinical risk narratives for Alzheimer's disease risk prediction, outperforming discrete grouping baselines.

DOT-MoE formulates dense layer decomposition as a differentiable optimal transport problem, enabling efficient training of sparse MoE models that retain 90% of original performance while reducing active parameters by 50%.

This paper introduces Differentiable Belief-based Opponent Shaping (D-BOS), a first-order method that treats observer beliefs as the shaped state and differentiates through belief update dynamics, allowing optimal strategies to emerge naturally from the environment's reward structure in hidden-role multi-agent settings.