Topographic Transformation as a Discrete Latent Variable

  title={Topographic Transformation as a Discrete Latent Variable},
  author={Nebojsa Jojic and Brendan J. Frey},
Invariance to topographic transformations such as translation and shearing in an image has been successfully incorporated into feedforward mechanisms, e.g., "convolutional neural networks", "tangent propagation". We describe a way to add transformation invariance to a generative density model by approximating the nonlinear transformation manifold by a discrete set of transformations. An EM algorithm for the original model can be extended to the new model by computing expectations over the set… CONTINUE READING
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