A differentiable generative evaluative network jointly learns graph partitions and QAOA parameter initializations, outperforming heuristic baselines on 101 of 183 tested QUBO, Ising, and MaxCut instances with zero-shot generalization.
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Neural QAOA$^{2}$: Differentiable Joint Graph Partitioning and Parameter Initialization for Quantum Combinatorial Optimization
A differentiable generative evaluative network jointly learns graph partitions and QAOA parameter initializations, outperforming heuristic baselines on 101 of 183 tested QUBO, Ising, and MaxCut instances with zero-shot generalization.