Reconciling shared versus context-specific information in a neural network model of latent causes
Qihong Lu,
Tan T. Nguyen,
Qiong Zhang
et al.
Abstract:It has been proposed that, when processing a stream of events, humans divide their experiences in terms of inferred latent causes (LCs) to support context-dependent learning. However, when shared structure is present across contexts, it is still unclear how the “splitting” of LCs and learning of shared structure can be simultaneously achieved. Here, we present the Latent Cause Network (LCNet), a neural network model of LC inference. Through learning, it naturally stores structure that is shared across tasks in… Show more
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