A campus-wide Journal Club covering topics of machine and deep learning. Everybody is cordially invited to join!
A campus-wide Journal Club covering topics of machine and deep learning. Everybody is cordially invited to join!
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.
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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@@ -9,21 +12,26 @@ If you’re interested in more details about the Journal Club, please subscribe
## Monday 20 January 10-11:30am
## Monday 20 January 10-11:30am
Venue: INM-1 Seminar room, building 15.9, room 4001b
Venue: **INM-1 Seminar room**, building 15.9, room 4001b
* Multi-Context Recurrent Neural Networks for Time Series Applications
* Multi-Context Recurrent Neural Networks for Time Series Applications <br>
https://publications.waset.org/3524/pdf
https://publications.waset.org/3524/pdf
* Global Sparse Momentum SGD for Pruning Very Deep Neural Networks
* Global Sparse Momentum SGD for Pruning Very Deep Neural Networks <br>
https://arxiv.org/pdf/1909.12778v3.pdf
https://arxiv.org/pdf/1909.12778v3.pdf
## Monday 16 December 10-11am
## Monday 16 December 10-11am
Venue: JSC, Rotunda, building 16.4, room 301
Venue: **JSC, Rotunda**, building 16.4, room 301
Our first Journal Club will cover two papers from ICCV 2019 about GANs.
Our first Journal Club will cover two papers from ICCV 2019 about GANs.
* 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
Please read
* COCO-GAN: Generation by Parts via Conditional Coordinating <br>
* 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
* COCO-GAN: Generation by Parts via Conditional Coordinating
full paper and supplementary material available at https://hubert0527.github.io/COCO-GAN/
full paper and supplementary material available at https://hubert0527.github.io/COCO-GAN/
