Christian Osendorfer

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NNAISENSE ∙ Technische Universität München

No Representation without Transformation

We propose to extend Latent Variable Models with a simple idea: learn to...
12/09/2019 ∙ by Giorgio Giannone, et al. ∙ 13 ∙ share

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Conditional Neural Style Transfer with Peer-Regularized Feature Transform

This paper introduces a neural style transfer model to conditionally gen...
06/07/2019 ∙ by Jan Svoboda, et al. ∙ 4 ∙ share

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Recurrent Neural Processes

We extend Neural Processes (NPs) to sequential data through Recurrent NP...
06/13/2019 ∙ by Timon Willi, et al. ∙ 2 ∙ share

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Differentiable Iterative Surface Normal Estimation

This paper presents an end-to-end differentiable algorithm for anisotrop...
04/15/2019 ∙ by Jan Eric Lenssen, et al. ∙ 2 ∙ share

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Improving approximate RPCA with a k-sparsity prior

A process centric view of robust PCA (RPCA) allows its fast approximate ...
12/29/2014 ∙ by Maximilian Karl, et al. ∙ 0 ∙ share

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On Fast Dropout and its Applicability to Recurrent Networks

Recurrent Neural Networks (RNNs) are rich models for the processing of s...
11/04/2013 ∙ by Justin Bayer, et al. ∙ 0 ∙ share

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Learning Sequence Neighbourhood Metrics

Recurrent neural networks (RNNs) in combination with a pooling operator ...
09/09/2011 ∙ by Justin Bayer, et al. ∙ 0 ∙ share

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Learning Stochastic Recurrent Networks

Leveraging advances in variational inference, we propose to enhance recu...
11/27/2014 ∙ by Justin Bayer, et al. ∙ 0 ∙ share

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Convolutional Neural Networks learn compact local image descriptors

A standard deep convolutional neural network paired with a suitable loss...
04/30/2013 ∙ by Christian Osendorfer, et al. ∙ 0 ∙ share

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Unsupervised Feature Learning for low-level Local Image Descriptors

Unsupervised feature learning has shown impressive results for a wide ra...
01/14/2013 ∙ by Christian Osendorfer, et al. ∙ 0 ∙ share

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NAIS-Net: Stable Deep Networks from Non-Autonomous Differential Equations

This paper introduces "Non-Autonomous Input-Output Stable Network" (NAIS...
04/19/2018 ∙ by Marco Ciccone, et al. ∙ 0 ∙ share

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Christian Osendorfer

Featured Co-authors

Jürgen Schmidhuber

Patrick van der Smagt

Jonathan Masci

Justin Bayer

Faustino Gomez

Nutan Chen

Maximilian Karl

Sebastian Urban

Jan Eric Lenssen

Marco Gallieri

Marco Ciccone

No Representation without Transformation

Conditional Neural Style Transfer with Peer-Regularized Feature Transform

Recurrent Neural Processes

Differentiable Iterative Surface Normal Estimation

Improving approximate RPCA with a k-sparsity prior

On Fast Dropout and its Applicability to Recurrent Networks

Learning Sequence Neighbourhood Metrics

Learning Stochastic Recurrent Networks

Convolutional Neural Networks learn compact local image descriptors

Unsupervised Feature Learning for low-level Local Image Descriptors

NAIS-Net: Stable Deep Networks from Non-Autonomous Differential Equations