Learning visual motion in recurrent neural networks

NeurIPS 2012 Marius PachitariuManeesh Sahani

We present a dynamic nonlinear generative model for visual motion based on a latent representation of binary-gated Gaussian variables. Trained on sequences of images, the model learns to represent different movement directions in different variables... (read more)

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