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Instance-Adaptive Video Compression: Improving Neural Codecs by Training on the Test Set


Nov 19, 2021
Ties van Rozendaal, Johann Brehmer, Yunfan Zhang, Reza Pourreza, Taco S. Cohen


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Skip-Convolutions for Efficient Video Processing


Apr 23, 2021
Amirhossein Habibian, Davide Abati, Taco S. Cohen, Babak Ehteshami Bejnordi

* CVPR 2021 

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A Combined Deep Learning based End-to-End Video Coding Architecture for YUV Color Space


Apr 01, 2021
Ankitesh K. Singh, Hilmi E. Egilmez, Reza Pourreza, Muhammed Coban, Marta Karczewicz, Taco S. Cohen

* 5 pages, submitted to as a conference paper. arXiv admin note: text overlap with arXiv:2103.01760 

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Transform Network Architectures for Deep Learning based End-to-End Image/Video Coding in Subsampled Color Spaces


Feb 27, 2021
Hilmi E. Egilmez, Ankitesh K. Singh, Muhammed Coban, Marta Karczewicz, Yinhao Zhu, Yang Yang, Amir Said, Taco S. Cohen

* 10 pages, submitted to an IEEE journal 

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Overfitting for Fun and Profit: Instance-Adaptive Data Compression


Jan 21, 2021
Ties van Rozendaal, Iris A. M. Huijben, Taco S. Cohen

* Accepted at ICLR 20201 

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Lossy Compression with Distortion Constrained Optimization


May 08, 2020
Ties van Rozendaal, Guillaume Sautière, Taco S. Cohen

* Accepted as a CVPR 2020 workshop paper: Workshop and Challenge on Learned Image Compression (CLIC) 

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A Data and Compute Efficient Design for Limited-Resources Deep Learning


Apr 21, 2020
Mirgahney Mohamed, Gabriele Cesa, Taco S. Cohen, Max Welling

* Accepted for poster presentation at the Practical Machine Learning for Developing Countries (PML4DC) workshop, ICLR 2020 

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Learning Discrete Distributions by Dequantization


Jan 30, 2020
Emiel Hoogeboom, Taco S. Cohen, Jakub M. Tomczak


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Video Compression With Rate-Distortion Autoencoders


Aug 14, 2019
Amirhossein Habibian, Ties van Rozendaal, Jakub M. Tomczak, Taco S. Cohen

* Accepted to ICCV 2019 

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Covariance in Physics and Convolutional Neural Networks


Jun 06, 2019
Miranda C. N. Cheng, Vassilis Anagiannis, Maurice Weiler, Pim de Haan, Taco S. Cohen, Max Welling


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Gauge Equivariant Convolutional Networks and the Icosahedral CNN


Feb 11, 2019
Taco S. Cohen, Maurice Weiler, Berkay Kicanaoglu, Max Welling


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Explorations in Homeomorphic Variational Auto-Encoding


Jul 12, 2018
Luca Falorsi, Pim de Haan, Tim R. Davidson, Nicola De Cao, Maurice Weiler, Patrick Forré, Taco S. Cohen

* 16 pages, 8 figures, ICML workshop on Theoretical Foundations and Applications of Deep Generative Models 

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Sample Efficient Semantic Segmentation using Rotation Equivariant Convolutional Networks


Jul 02, 2018
Jasper Linmans, Jim Winkens, Bastiaan S. Veeling, Taco S. Cohen, Max Welling

* Presented at the ICML workshop: Towards learning with limited labels: Equivariance, Invariance, and Beyond, 2018 

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3D G-CNNs for Pulmonary Nodule Detection


Apr 12, 2018
Marysia Winkels, Taco S. Cohen


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Intertwiners between Induced Representations (with Applications to the Theory of Equivariant Neural Networks)


Mar 30, 2018
Taco S. Cohen, Mario Geiger, Maurice Weiler


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HexaConv


Mar 06, 2018
Emiel Hoogeboom, Jorn W. T. Peters, Taco S. Cohen, Max Welling


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Spherical CNNs


Feb 25, 2018
Taco S. Cohen, Mario Geiger, Jonas Koehler, Max Welling

* Proceedings of the 6th International Conference on Learning Representations (ICLR), 2018 

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A New Method to Visualize Deep Neural Networks


Jun 12, 2017
Luisa M. Zintgraf, Taco S. Cohen, Max Welling

* Please note that this version of the article is outdated. The new version (published at ICLR2017) includes additional experiments on MRI scans and can be found at arXiv:1702.04595 

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Steerable CNNs


Dec 27, 2016
Taco S. Cohen, Max Welling


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Group Equivariant Convolutional Networks


Jun 03, 2016
Taco S. Cohen, Max Welling

* Proceedings of the International Conference on Machine Learning (ICML), 2016 

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Harmonic Exponential Families on Manifolds


May 20, 2015
Taco S. Cohen, Max Welling

* fixed typo 

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Transformation Properties of Learned Visual Representations


Apr 07, 2015
Taco S. Cohen, Max Welling

* T.S. Cohen & M. Welling, Transformation Properties of Learned Visual Representations. In International Conference on Learning Representations (ICLR), 2015 

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