Hierarchical Mixture of Classification Experts Uncovers Interactions between Brain Regions

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Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer (2017, background): “Other work has focused on different expert configurations such as a hierarchical structure (Yao et al., 2009), infinite numbers of experts (Rasmussen & Ghahramani, 2002), and adding experts sequentially (Aljundi et al.”
A modeling framework for adaptive lifelong learning with transfer and savings through gating in the prefrontal cortex (2020, background): “Some studies have provided evidence for such a functional architecture in the brain [27], and prefrontal cortical areas in particular [28],[29],[30].”
XNAS: Neural Architecture Search with Expert Advice (2019, background): “Mentions of Experts in deep learning [32, 52, 11, 1] literature go decades back [18, 5], typically combining models as separable experts sub-models.”
Twenty Years of Mixture of Experts (2012, methodology): “D object recognition [122], image transport regression [30], deformable model fitting [11], filter selection [123], nonlinear system identification of a robotic arm [113], connectivity analysis in the brain from fMRI (functional magnetic resonance imaging) data [13], 3-”
Prior Knowledge Improves Decoding of Finger Flexion from Electrocorticographic Signals (2011, methodology): “, 2007) as well as neural computation (Yao et al., 2009).”