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Found 3 papers, 2 papers with code
Meta-Learned Models of Cognition
Meta-learning is a framework for learning learning algorithms through repeated interactions with an environment as opposed to designing them by hand.
A flow-based latent state generative model of neural population responses to natural images
We present a joint deep neural system identification model for two major sources of neural variability: stimulus-driven and stimulus-conditioned fluctuations.
Generalization in data-driven models of primary visual cortex
With this new readout we train our network on neural responses from mouse primary visual cortex (V1) and obtain a gain in performance of 7% compared to the previous state-of-the-art network.
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