Learning from Pattern Completion: Self-supervised Controllable Generation

Neural Information Processing Systems 

Inspired by the neural mechanisms that may contribute to the brain's associative power, specifically the cortical modularization and hippocampal pattern completion, here we propose a self-supervised controllable generation (SCG) framework.

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