Topic: task inference

Animals thrive in a constantly changing environment and leverage the temporal structure to learn well-factorized causal representations. In contrast, traditional neural networks have no representation of these changes and suffer from forgetting. In the prefrontal-thalamic circuit, reciprocal feedback connections produce a compressed thalamic representation of the computations performed in the prefrontal cortex. In inspiration, we use a neural network with a separate latent task representation and introduce a simple algorithm that uses optimization to rapidly infer and generate representations