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MoQ-NAS

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A flexible framework for Multi-Objective Neural Architecture Search (NAS) in PyTorch. It implements and compares Quantum-Inspired (MO-QNAS) and classic Evolutionary Algorithms (GA, NSGA-II, NSGA-III) to optimize CNNs for multiple objectives like accuracy, model size, and inference time. Includes a module for post-hoc fairness evaluation.

Creat2025-03-26T23:08:57
Update2025-11-07T06:20:37
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