A monotone co-design framework for neural network processors that treats uncertainty via Confidence as a tunable resource and allows modular block refinement without structural changes.
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Uncertainty-Aware End-to-End Co-Design of Neural Network Processors: From Training and Mapping to Fabrication
A monotone co-design framework for neural network processors that treats uncertainty via Confidence as a tunable resource and allows modular block refinement without structural changes.