Zhikun Chu — accepted AI-conference papers

2025

Shaping Sequence Attractor Schema in Recurrent Neural Networks

Zhikun Chu, Bo Hong, Xiaolong Zou, Yuanyuan Mi

NeurIPS 2025poster

Sequence schemas are abstract, reusable knowledge structures that facilitate rapid adaptation and generalization in novel sequential tasks. In both animals and humans, shaping is an efficient way for acquiring such schemas, particularly in complex sequential tasks. As a form of curriculum learning,…

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2023

Learning and processing the ordinal information of temporal sequences in recurrent neural circuits

Xiaolong Zou, Zhikun Chu, Qinghai Guo, Jie Cheng, Bo Hong, Si Wu +1

NeurIPS 2023poster

Temporal sequence processing is fundamental in brain cognitive functions. Experimental data has indicated that the representations of ordinal information and contents of temporal sequences are disentangled in the brain, but the neural mechanism underlying this disentanglement remains largely unclea…

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