Cirq/PyTorch implementation of Quantum Architecture Search via Deep Reinforcement Learning by (Kuo et al., 2021)
Code for Kolmogorov-Arnold Network for Quantum Architecture Search i.e., KANQAS
A curated list of standout libraries, projects, tutorials, influential research papers, and essential resources focused on Quantum Architecture Search (QAS). This collection is designed to serve as a structured and thorough reference, empowering researchers and developers to accelerate their work and stay at the forefront of QAS advancements
[NeurIPS 2025] Tensor network with RL for improved QAS
Surrogate benchmark for QAS. Includes code, datasets, and tools for fast evaluation and integration into custom QAS pipelines.
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