The hybrid BOCS-GP method with adaptive LCB selection finds better objective values than random-point addition in QUBO and HUBO by selecting points that promote search progress within Hamming-distance neighborhoods.
Benchmark test of black-box optimiza- tion using d-wave quantum annealer
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NIMS-OS is an open-source Python framework that orchestrates AI modules (Bayesian optimization, phase diagram construction) with robotic hardware (NAREE) to enable autonomous closed-loop materials exploration.
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Improving search efficiency via adaptive acquisition function selection in discrete black-box optimization
The hybrid BOCS-GP method with adaptive LCB selection finds better objective values than random-point addition in QUBO and HUBO by selecting points that promote search progress within Hamming-distance neighborhoods.
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NIMS-OS: An automation software to implement a closed loop between artificial intelligence and robotic experiments in materials science
NIMS-OS is an open-source Python framework that orchestrates AI modules (Bayesian optimization, phase diagram construction) with robotic hardware (NAREE) to enable autonomous closed-loop materials exploration.