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action optimization » reaction optimization (Expand Search), function optimization (Expand Search), codon optimization (Expand Search)
art optimization » swarm optimization (Expand Search), after optimization (Expand Search), path optimization (Expand Search)
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based action » based motion (Expand Search), based active (Expand Search), based fusion (Expand Search)
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action optimization » reaction optimization (Expand Search), function optimization (Expand Search), codon optimization (Expand Search)
art optimization » swarm optimization (Expand Search), after optimization (Expand Search), path optimization (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
based action » based motion (Expand Search), based active (Expand Search), based fusion (Expand Search)
based art » based care (Expand Search)
lens » less (Expand Search)
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Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf
Published 2020“…And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. …”
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Minisymposterium: Muq-Hippylib: A Bayesian Inference Software Framework Integrating Data with Complex Predictive Models under Uncertainty
Published 2021“…In this poster, we present an extensible software framework MUQ-hIPPYlib that overcomes this hurdle by providing unprecedented access to state-of-the-art algorithms for Bayesian inverse problems. MUQ provides a spectrum of powerful Bayesian inversion models and algorithms, but expects forward models to come equipped with gradients/Hessians to permit large-scale solution. hIPPYlib implements powerful large-scale gradient/Hessian-based solvers in an environment that can automatically generate needed derivatives, but it lacks full Bayesian capabilities. …”
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SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion
Published 2020“…The central questions are: How do we optimally learn from data through the lens of models? …”
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SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion
Published 2020“…The central questions are: How do we optimally learn from data through the lens of models? …”