I looked up if any posts have mentioned Simons Institute youtube channel, and only found 3 results. The seminar seems to provide the very valuable knowledge in a concise matter than reading a whole paper. Each presenter is very talented from essentially prestigious institutions and speaks very well.

But I wonder why I haven’t seen the discussion on it here.

Finally, after almost two years of development, we are excited to release our toolbox for deep probabilistic inference!

https://brancher.org

Brancher is designed to make the integration between Bayesian statistics and deep learning easy and intuitive. We have prepared tutorials and examples in Google Colab: https://brancher.org/#examples | https://brancher.org/#tutorials

We are curious about your feedback! Either here or on Twitter: @pybrancher

This is a simple project I started a few months ago to organize machine learning projects. I’ve recently added PyTorch support to it and updated the documentations.

https://github.com/vpj/lab

It helps you organize experiment results, checkpoints and summaries, and takes care of console outputs.

I’m working on cleaning up the API a little more.

https://slideslive.com/icml https://facebook.com/pg/icml.imls/videos/

Full disclosure, this isn’t my project. I volunteer for a Seattle based nonprofit that puts on speaking events.

One of our speakers did a 5 minute talk about a cat door he created using machine learning.

His cat was bringing in dead animals to the house, so he created a cat door that will automatically lock for 15 minutes when the cat has something in its mouth. To do this he connected a camera to the cat door and used machine learning to check the image of the cat and whether the door should be locked or not.

Presentation is here if I’ve piqued your interest: https://youtu.be/1A-Nf3QIJjM

For five years I have been playing with reinforcement learning and some computer graphic, but recently I decided to give up all my previous researches and begin my journey on attention and saliency. It seems that it is easy to make massive CVPR publications every year by combining modules, for example:

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(please pay attention to the paper title and the first (or join-first) author “W. Wang”)

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CVPR 2019:

Salient object detection with pyramid attention and salient edges

W. Wang*, S. Zhao*, S. Hoi, J. Shen, and A. Borji.

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CVPR 2019:

An iterative and cooperative top-down and bottom-up inference network for salient object detection

W. Wang, J. Shen, M.-M. Cheng, and L. Shao.

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CVPR 2019:

Shifting more attention to video salient object detection

D. Fan, W. Wang, M.-M. Cheng, and J. Shen

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CVPR 2019:

See more, know more: Unsupervised video object segmentation with co-attention siamese networks

X. Lu*, W. Wang*, C. Ma, J. Shen, L. Shao and F. Porikli

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CVPR 2019:

Learning unsupervised video object segmentation through visual attention

W. Wang*, H. Song*, S. Zhao, J. Shen, S. Zhao, S. Hoi, and H. Ling

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CVPR 2019:

Reasoning visual dialogs with structural and partial observations

Z. Zheng*, W. Wang*, S. Qi*, and S.-C. Zhu

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CVPR 2018:

Inferring shared attention in social scene videos

L. Fan, Y. Chen, P. Wei, W. Wang

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CVPR 2018:

Salient object detection driven by fixation prediction

W. Wang, J. Shen and A. Borji

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CVPR 2018:

Revisiting video saliency: A large-scale benchmark and a new model

W. Wang, J. Shen, F. Guo, M.-M. Cheng, and A. Borji

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CVPR 2018:

Attentive fashion grammar network for fashion landmark detection and clothing category classification

W. Wang*, Y. Xu*, J. Shen, and S.-C. Zhu

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…（much more hidden）

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I think I HAVE to give up all my previous researches and start my works on attention and saliency, otherwise all my job and teaching opportunities will disappear because these people are so “talented”.

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Edited:

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OK. Here I would like to add some suggestions to make this post constructive. I strongly recommend IEEE CVPR to have a longer and a more meaningful PC meeting, maybe somehow like that of SIGGRAPH, to have some discussion on the “multiple submission” issue.

The author has decided not to release the model. Read here: https://medium.com/@NPCollapse/the-hacker-learns-to-trust-62f3c1490f51

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Excerpt from the post:

I have decided to not release my model, and explain why below. I have also written a small addendum answering some questions about my model and its quality. I would like to thank every single person that engaged with me and helped me come to these conclusions. I have learned so much and could never have done it on my own. Thank you.