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[[Home](Home)]
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A campus-wide Journal Club covering topics of machine and deep learning. Everybody is cordially invited to join!
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We discuss most recent papers from the field, e.g., recent network architectures and their applications. For each meeting we pick two papers, everybody reads them and prepares his/her questions and comments. In the Journal Club there will be a short intro to the papers followed by a joint discussion.
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| ... | ... | @@ -9,21 +12,26 @@ If you’re interested in more details about the Journal Club, please subscribe |
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## Monday 20 January 10-11:30am
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Venue: INM-1 Seminar room, building 15.9, room 4001b
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Venue: **INM-1 Seminar room**, building 15.9, room 4001b
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* Multi-Context Recurrent Neural Networks for Time Series Applications
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* Multi-Context Recurrent Neural Networks for Time Series Applications <br>
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https://publications.waset.org/3524/pdf
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* Global Sparse Momentum SGD for Pruning Very Deep Neural Networks
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* Global Sparse Momentum SGD for Pruning Very Deep Neural Networks <br>
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https://arxiv.org/pdf/1909.12778v3.pdf
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## Monday 16 December 10-11am
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Venue: JSC, Rotunda, building 16.4, room 301
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Venue: **JSC, Rotunda**, building 16.4, room 301
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Our first Journal Club will cover two papers from ICCV 2019 about GANs.
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Please read
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* SinGAN: Learning a Generative Model from a Single Natural Image (Best Paper Award) http://openaccess.thecvf.com/content_ICCV_2019/papers/Shaham_SinGAN_Learning_a_Generative_Model_From_a_Single_Natural_Image_ICCV_2019_paper.pdf
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* COCO-GAN: Generation by Parts via Conditional Coordinating
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Our first Journal Club will cover two papers from ICCV 2019 about GANs.
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* SinGAN: Learning a Generative Model from a Single Natural Image (Best Paper Award) <br> http://openaccess.thecvf.com/content_ICCV_2019/papers/Shaham_SinGAN_Learning_a_Generative_Model_From_a_Single_Natural_Image_ICCV_2019_paper.pdf
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* COCO-GAN: Generation by Parts via Conditional Coordinating <br>
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full paper and supplementary material available at https://hubert0527.github.io/COCO-GAN/
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[[Home](Home)]
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last change: 13.1.2020 sw |
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