Emergence of Complex-Like Cells in a Temporal Product Network with Local Receptive Fields

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Slow feature analysis yields a rich repertoire of complex cell properties

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Learning generative visual models from few training examples: An incremental bayesian approach tested on 101 object categories

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Fast inference in sparse coding algorithms with applications to object recognition

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Why is real-world visual object recognition hard

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Slow, decorrelated features for pretraining complex cell-like networks

What is the best multi-stage architecture for object recognition?

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Learning invariant features through topographic filter maps

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Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations

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A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation

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Factored conditional restricted Boltzmann Machines for modeling motion style

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