Niching importance sampling yields a robust probability-of-failure estimator that avoids degeneracy on multi-modal performance functions by integrating evolutionary niching with importance sampling.
Feasibility of Detecting Potential Emergencies in Symbiotic Human-Robot Collaboration with a mobile EEG,
2 Pith papers cite this work, alongside 34 external citations. Polarity classification is still indexing.
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DS-MTNet uses frequency-constrained source decomposition and reusable information slots to jointly decode three EEG-based cognitive readouts in a driving task, outperforming single-task and multi-task baselines.
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Niching Importance Sampling for Multi-modal Rare-event Simulation
Niching importance sampling yields a robust probability-of-failure estimator that avoids degeneracy on multi-modal performance functions by integrating evolutionary niching with importance sampling.
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DS-MTNet:Structured Multi-Task EEG Decoding for Human-Machine Collaboration
DS-MTNet uses frequency-constrained source decomposition and reusable information slots to jointly decode three EEG-based cognitive readouts in a driving task, outperforming single-task and multi-task baselines.