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Results show that an AI scientist workflow can propose thermal structures, test them under common constraints, and quantify their electrical cost, and show that lower temperature can accompany higher thermal resistance when current falls.
M-Net achieves up to a 12.37% improvement in segmentation accuracy by integrating mathematical features into deep learning architectures, challenging the notion that data alone suffices for optimal performance.
