Deconvolutional networks Deconvolutional networks
Paper summary _Objective:_ Define a new deconvolution layer. #### Results: Not really interesting except from the fact that it first introduces **deconvolution layers** which are very ill-name as they are not actual deconvolution but instead a **transposed convolution** or also called a **fractionally strided convolutions**. [![Deconvolutional layer](https://cloud.githubusercontent.com/assets/17261080/25344392/44693b48-2912-11e7-8dda-2b64d99292a9.gif)](https://cloud.githubusercontent.com/assets/17261080/25344392/44693b48-2912-11e7-8dda-2b64d99292a9.gif) Visualization for other operations can be seen [here](https://github.com/vdumoulin/conv_arithmetic) corresponding to [A guide to convolution arithmetic for deep learning](https://arxiv.org/pdf/1603.07285.pdf).

Summary by Léo Paillier 11 months ago
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