Chengxu Zhuang

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We propose a new neurally-inspired model that can learn to encode global relationship context of visual events across time and space and to use the contex-tual information to modulate the analysis by synthesis process in a predictive coding framework. The model is based on the principle of mutual predictability. It learns latent contextual representations(More)
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