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Found 2 essays matching the above criteria.
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1. More efficient training using equivariant neural networks
University essay from Uppsala universitet/Avdelningen Vi3Abstract : Convolutional neural networks are equivariant to translations; equivariance to other symmetries, however, is not defined and the class output may vary depending on the input's orientation. To mitigate this, the training data can be augmented at the cost of increased redundancy in the model. READ MORE
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2. Group Invariant Convolutional Boltzmann Machines
University essay from Göteborgs universitet/Institutionen för matematiska vetenskaperAbstract : We investigate group invariance in unsupervised learning in the context of certain generative networks based on Boltzmann machines. Specifically, we introduce a generalization of restricted Boltzmann machines which is adapted to input data that is acted upon by any compact group G. READ MORE