«AutoQML, self-assembling circuits, hyper-parameterized Quantum ML platform, using cirq, tensorflow and tfq. Trillions of possible qubit registries, gate combinations and moment sequences, ready to be adapted into your ML flow. Here I demonstrate climatechange, jameswebbspacetelescope and microbiology vision applications… [Thus far, a circuit with 16-Qubits and a gate sequence of [ YY ] – [ XX ] – [CNOT] has performed the best, per my blend of metrics…]».
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703-712(August 2017)Propensity score; Classification trees; Machine learning.
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Y. Ma, D. Tsao, and H. Shum. (2022)cite arxiv:2207.04630Comment: 24 pages, 11 figures. This updated version makes changes in languages and adds a few additional references. This is the final version to be published.