09# our-daily-paper Paper List I have read or will read, just to keep control.
Every time I read the paper, I will put an record containing last read and amount of times I have read this specific paper.
- CNN Features off-the-shelf: an Astounding Baseline for Recognition | last = (23/09/2018) | cont=1 |
- Deep Neural Networks for YouTube Recommendations | last = (15/08/2018) | cont=1 |
- AR-MDN: Associative and Recurrent Mixture Density Networks for eRetail Demand Forecasting | last = (15/08/2018) | cont=2 |
- irst-order Meta-Learned Initialization for Faster Adaptation in Deep Reinforcement Learning | last = (17/08/2018) | cont=1 |
- https://arxiv.org/pdf/1310.1531.pdf
- https://arxiv.org/pdf/1411.1792.pdf
- https://arxiv.org/abs/1312.6199
- https://arxiv.org/abs/1311.2524
- https://arxiv.org/abs/1311.2901
- https://arxiv.org/abs/1312.6034
- https://arxiv.org/abs/1412.6806
- https://arxiv.org/abs/1412.0035
- http://papers.nips.cc/paper/5420-do-convnets-learn-correspondence.pdf
- https://berkeley-deep-learning.github.io/cs294-131-s17/ (IT ALL)
- https://arxiv.org/abs/1412.6572