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Found 3 papers, 1 papers with code
Harmonizing Program Induction with Rate-Distortion Theory
Many aspects of human learning have been proposed as a process of constructing mental programs: from acquiring symbolic number representations to intuitive theories about the world.
Modelling continual learning in humans with Hebbian context gating and exponentially decaying task signals
Here, we propose novel computational constraints for artificial neural networks, inspired by earlier work on gating in the primate prefrontal cortex, that capture the cost of interleaved training and allow the network to learn two tasks in sequence without forgetting.
Episodic memory for continual model learning
Alternatively, maintaining only a limited set of models in memory could limit memory requirements.
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