Gaussian-process-based Bayesian optimization for neurostimulation interventions in rats
Author:
Funder
NSERC
IVADO
Publisher
Elsevier BV
Reference19 articles.
1. Autonomous optimization of neuroprosthetic stimulation parameters that drive the motor cortex and spinal cord outputs in rats and monkeys;Bonizzato;Cell Rep. Med.,2023
2. Hierarchical Bayesian Optimization of Spatiotemporal Neurostimulations for Targeted Motor Outputs;Laferriere;IEEE Trans. Neural Syst. Rehabil. Eng.,2020
3. Automated deep brain stimulation programming with safety constraints for tremor suppression in patients with Parkinson's disease and essential tremor;Sarikhani;J. Neural. Eng.,2022
4. Efficient TMS-Based Motor Cortex Mapping Using Gaussian Process Active Learning;Faghihpirayesh;IEEE Trans. Neural Syst. Rehabil. Eng.,2021
5. Bayesian optimization of peripheral intraneural stimulation protocols to evoke distal limb movements;Losanno;J. Neural. Eng.,2021
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Forgotten Tides: A Novel Strategy for Bayesian Optimization of Neurostimulation;Epilepsy Currents;2024-05-30
2. Optimal Placement of High-Channel Visual Prostheses in Human Retinotopic Visual Cortex;2024-03-11
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