Learned-Weight Ensemble Monte Carlo DropBlock for Uncertainty Estimation and EEG Classification
Reliable predictive uncertainty—in particular predictive entropy used at decision time—in motor imagery electroencephalography (EEG)-based brain–computer interfaces (BCIs) is critical for safe real-world operation. Although Monte Carlo dropout and deep ensembles are effective fo...
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| Автори: | , , , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
IEEE
2025-01-01
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| Серія: | IEEE Open Journal of Instrumentation and Measurement |
| Предмети: | |
| Онлайн доступ: | https://ieeexplore.ieee.org/document/11271584/ |
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