604 citations · 1.7k across the 67 of their papers we have counts for
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On Fast Dropout and its Applicability to Recurrent Networks
Justin Bayer, Christian Osendorfer, Daniela Korhammer +3
Recurrent Neural Networks (RNNs) are rich models for the processing of sequential data. Recent work on advancing the state of the art has been focused on the optimization or modell…
Convolutional Neural Networks learn compact local image descriptors
Christian Osendorfer, Justin Bayer, Patrick van der Smagt
A standard deep convolutional neural network paired with a suitable loss function learns compact local image descriptors that perform comparably to state-of-the art approaches.
Unsupervised Feature Learning for low-level Local Image Descriptors
Christian Osendorfer, Justin Bayer, Sebastian Urban +1
Unsupervised feature learning has shown impressive results for a wide range of input modalities, in particular for object classification tasks in computer vision. Using a large amo…